Medical monitoring system

ABSTRACT

Medical patient monitoring devices that have the capability of detecting the physical proximity of a clinician are disclosed. The medical patient monitoring devices may be configured to perform a first selected action when the presence of a clinician is detected in a first detection area, and to perform a second selected action when the presence of the clinician is detected in a second detection area. The medical patient monitoring devices may be configured to determine whether a clinician is present in a detection area based on the strength of a signal from a clinician token, and based on a signal strength adjustment value associated with the clinician token. When the presence of a clinician is detected in a detection area, the medical patient monitoring devices may be configured to perform a predetermined action that is determined from a remote database communicatively coupled thereto.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application is a continuation of U.S. application Ser. No.16/042,913, filed Jul. 23, 2018, and entitled “MEDICAL MONITORINGSYSTEM,” which is a continuation of U.S. application Ser. No.12/904,377, filed Oct. 14, 2010, and entitled “MEDICAL MONITORINGSYSTEM,” which is a continuation-in-part of U.S. application Ser. No.12/717,081, filed Mar. 3, 2010, and entitled “MEDICAL MONITORINGSYSTEM,” which claims a priority benefit to U.S. Provisional Application61/209,147, filed Mar. 4, 2009, and entitled “PROXIMITY DISPLAYMONITOR,” and to U.S. Provisional Application 61/296,439, filed Jan. 19,2010, and entitled “MEDICAL MONITORING SYSTEM,” the entire contents ofeach of which are hereby incorporated by reference herein.

BACKGROUND Field of the Invention

This disclosure relates to systems, devices, and methods withapplications in, for example, hospitals and other patient carefacilities. For example, the systems, devices, and methods describedherein can be used for acquiring physiological information frompatients, analyzing the physiological information, and communicating thephysiological information to clinicians and other systems or devices.

Description of the Related Art

Hospitals, nursing homes, and other patient care facilities typicallyinclude patient monitoring devices at one or more bedsides in thefacility. Patient monitoring devices generally include sensors,processing equipment, and displays for obtaining and analyzing a medicalpatient's physiological parameters. Physiological parameters include,for example, respiratory rate, SpO₂ level, pulse, and blood pressure,among others. Clinicians, including doctors, nurses, and certain othermedical personnel use the physiological parameters obtained from themedical patient to diagnose illnesses and to prescribe treatments.Clinicians also use the physiological parameters to monitor a patientduring various clinical situations to determine whether to increase thelevel of medical care given to the patient.

Patient monitors capable of measuring pulse oximetry parameters, such asSpO2 and pulse rate in addition to advanced parameters, such as HbCO,HbMet and total hemoglobin (Hbt) and corresponding multiple wavelengthoptical sensors are described in at least U.S. patent application Ser.No. 11/367,013, filed Mar. 1, 2006 and entitled Multiple WavelengthSensor Emitters and U.S. patent application Ser. No. 11/366,208, filedMar. 1, 2006 and entitled Noninvasive Multi-Parameter Patient Monitor,both assigned to Masimo Laboratories, Irvine, Calif. (Masimo Labs) andboth incorporated by reference herein. Further, noninvasive bloodparameter monitors and corresponding multiple wavelength opticalsensors, such as Rainbow™ adhesive and reusable sensors and RAD-57™ andRadical-7™ monitors for measuring SpO2, pulse rate, perfusion index,signal quality, HbCO and HbMet among other parameters are also availablefrom Masimo Corporation, Irvine, Calif. (Masimo).

Advanced physiological monitoring systems may incorporate pulse oximetryin addition to advanced features for the calculation and display ofother blood parameters, such as carboxyhemoglobin (HbCO), methemoglobin(HbMet) and total hemoglobin (Hbt), as a few examples. Advancedphysiological monitors and corresponding multiple wavelength opticalsensors capable of measuring parameters in addition to SpO2, such asHbCO, HbMet and Hbt are described in at least U.S. patent applicationSer. No. 11/367,013, filed Mar. 1, 2006, titled Multiple WavelengthSensor Emitters and U.S. patent application Ser. No. 11/366,208, filedMar. 1, 2006, titled Noninvasive Multi-Parameter Patient Monitor,assigned to Masimo Labs and incorporated by reference herein. Further,noninvasive blood parameter monitors and corresponding multiplewavelength optical sensors, such as Rainbow™ adhesive and reusablesensors and RAD-57™ and Radical-7™ monitors for measuring SpO2, pulserate, perfusion index (PI), signal quality (SiQ), pulse variabilityindex (PVI), HbCO and HbMet among other parameters are also availablefrom Masimo.

SUMMARY OF THE INVENTION

Various medical monitoring devices, systems, and methods are describedherein. In some embodiments, a medical monitoring device or system iscapable of detecting the presence of a clinician and, for example,taking some action in response to detection of the clinician's presence.In some embodiments, a medical monitoring system is capable of detectingthe location of a number of medical devices, clinicians, and/or patientsin a hospital or other patient care facility. The detected locations canthen be used to take some location-based action, such as, for example,changing the configuration of a medical device.

In some embodiments, a medical patient monitoring device for monitoringphysiological information comprises: an interface configured to receivephysiological information associated with at least one patient; and adetector for detecting the physical presence of a clinician token withinfirst and second detection areas in the vicinity of the medical patientmonitoring device, the clinician token being indicative of the identityof a clinician, wherein the medical patient monitoring device furthercomprises a processor that is configured to take a first predeterminedaction in response to detection of the clinician token in the firstdetection area, and to take a second predetermined action in response todetection of the clinician token in the second detection area, the firstand second predetermined actions being associated with the identity ofthe clinician.

In some embodiments, a medical patient monitoring device for monitoringphysiological information comprises: an interface configured to receivephysiological information associated with at least one patient; and adetector for detecting the physical presence of a clinician token withina detection area in the vicinity of the medical patient monitoringdevice, the clinician token being indicative of the identity of aclinician, wherein the medical patient monitoring device furthercomprises a processor that is configured to take a predetermined actionin response to detection of the clinician token in the detection area,the predetermined action being associated with the identity of theclinician, and wherein the processor is further configured to determinewhether the clinician token is present within the detection area basedon the strength of a signal from the clinician token, and based on asignal strength adjustment value associated with the clinician token.

In some embodiments, a medical patient monitoring device for monitoringphysiological information comprises: an interface configured to receivephysiological information associated with at least one patient; and adetector for detecting the physical presence of a clinician token withina detection area in the vicinity of the medical patient monitoringdevice, the clinician token being indicative of the identity of aclinician, wherein the medical patient monitoring device furthercomprises a processor that is configured to take a predetermined actionin response to detection of the clinician token in the detection area,the predetermined action being associated with the identity of theclinician, and wherein the predetermined action is determined from adatabase that is remotely communicatively coupled to the medical patientmonitoring device via a communication network.

BRIEF DESCRIPTION OF THE DRAWINGS

Various embodiments will be described hereinafter with reference to theaccompanying drawings. These embodiments are illustrated and describedby example only, and are not intended to limit the scope of thedisclosure.

FIG. 1 is an exemplary block diagram showing a physiological monitoringsystem according to an embodiment of the present invention;

FIG. 2 is an exemplary block diagram showing another embodiment of aphysiological monitoring system;

FIG. 3 is an exemplary block diagram showing a network interface moduleaccording to an embodiment of the present invention;

FIG. 4 is an exemplary flowchart diagram showing a process forcontext-based communication of physiological information according to anembodiment of the present invention; and

FIG. 5 is an exemplary block diagram showing an alarm notificationsystem according to an embodiment of the present invention.

FIG. 6 is a block diagram illustrating an embodiment of a clinicalnetwork environment;

FIG. 7 is a block diagram illustrating a more detailed embodiment of theclinical network environment of FIG. 6;

FIG. 8A is a flow chart illustrating an embodiment of a process forjournaling medical events in a journal database;

FIG. 8B is a flow chart illustrating an embodiment of a process forcorrelating data from the journal database and the round-robin database;

FIG. 9 is a screen shot of an example user interface for monitoringpatients in the clinical network environment of FIG. 6;

FIG. 10 is a perspective view of an advanced patient-monitoring system;

FIG. 11 illustrates a proximity display in a multi-user environment;

FIG. 12 is a general block diagram of a proximity display monitor;

FIG. 13 illustrates a user display preference screen;

FIG. 14 is a schematic diagram of a patient monitoring device that iscapable of automatically detecting the presence of a clinician token;

FIG. 15 is a flowchart illustrating detection method for detecting thepresence of a clinician token within the detection region of a patientmonitoring device;

FIG. 16 illustrates an example graphical user interface of nurses'station or a central patient monitoring station;

FIG. 17 is a flowchart illustrating a method for determining when todisable a clinician-specific action that had been previously enabled bya patient monitoring device based upon the detected presence of theclinician;

FIG. 18 is a schematic diagram of a system for enabling a patientmonitoring device to automatically detect the presence of a cliniciantoken;

FIG. 19 is a schematic illustration of a patient monitoring devicenetwork having a clinician proximity awareness feature;

FIG. 20 is a schematic drawing of a hospital floor with distributed WiFiaccess points that can be used to estimate the physical locations ofmedical devices, patients, and clinicians;

FIGS. 21A-F, 22A-E, and 23A-C illustrate proximity display embodimentsthat advantageously provide user proximity feedback;

FIGS. 21A-F illustrate a proximity display embodiment utilizing avirtual rotating triangular solid for proximity feedback;

FIGS. 22A-E illustrate a proximity display embodiment utilizing avirtual rotating cube for proximity feedback;

FIGS. 23A-C illustrate proximity display embodiment utilizing a virtualrotating planar solid for proximity feedback;

FIG. 24A illustrates a first medical device and a second medical devicethat communicate with one another via a translation module;

FIG. 24B illustrates a first medical device and a second medical devicethat communicate with one another via a translation module and acommunication bus;

FIG. 25A illustrates an example input message received by thetranslation module;

FIG. 25B illustrates a message header segment of the input message ofFIG. 19A that has been parsed into fields;

FIG. 25C illustrates an encoded version of the parsed message headersegment of FIG. 25B;

FIG. 25D illustrates an example output message of the translation modulebased on the input message of FIG. 25A;

FIG. 26 illustrates a translation process for generating an outputmessage based on an input message and a comparison with translationrules associated with the translation module;

FIG. 27A illustrates a translation process in which the translationmodule facilitates communication of an HL7 message from a HospitalInformation System (“HIS”) having a first HL7 format to an intendedrecipient medical device having a second HL7 format;

FIG. 27B illustrates a translation process in which the translationmodule facilitates communication of an HL7 message from a medical devicehaving a first HL7 format to a HIS having a second HL7 format;

FIG. 28 illustrates an example screenshot from a messagingimplementation software tool for manually configuring translation rulesto be used by the translation module;

FIGS. 29A and 29B illustrate automatic rule configuration processesperformed by the translation module;

FIGS. 29C and 29D illustrate automatic rule configuration processesperformed by the translation module for messages utilizing the HL7protocol;

FIG. 30 is an example graph of the distribution of alarm events for agiven physiological parameter as a function of alarm limit values;

FIG. 31 is a flow chart that illustrates a method for determining thevariation in identified alarm conditions resulting from varying alarmcriteria;

FIG. 32 illustrates an example report with a table showing how simulatedalarm criteria affect alarm detection events;

FIG. 33 is a flow chart that illustrates another method for determiningthe variation in identified alarm conditions that occur as a result ofvarying alarm criteria;

FIG. 34 illustrates an example report with a table showing how simulatedalarm criteria affect the number of alarm detection events as well ashow the simulated alarm criteria affect, for example, false negativesand false positives;

FIG. 35 is a flow chart that illustrates a method for determining thevariation in alarm notification events that occurs as a result ofvarying alarm notification delay times;

FIGS. 36A-B, 37A-F, 38A-B, 39A-B, 40A-B, 41, 42, and 43A-B illustrateproximity displays that provide advantageous features in multi-userpatient-monitoring environment;

FIGS. 36A-B illustrate displays having layout zones;

FIGS. 37A-F illustrate displays that vary layouts and font sizesaccording to the number of installed parameters;

FIGS. 38A-B illustrate displays having parameter wells;

FIGS. 39A-B illustrate displays that enlarge alarming parameters;

FIGS. 40A-B illustrates displays of trend graphs having colored alarmzones;

FIG. 41 illustrate a display that inverts arrow keys to match thecursor;

FIG. 42 illustrates a display having user-selectable jump-screens; and

FIGS. 43A-B illustrate trend graph displays.

DETAILED DESCRIPTION

In various embodiments, physiological monitoring systems are systemsthat monitor physiological signals generated by a medical patient andprocess the signals to determine any of a variety of physiologicalparameters of the patient. For example, in some cases, a physiologicalmonitoring system can determine any of a variety of physiologicalparameters of a patient, including respiratory rate, inspiratory time,expiratory time, i:e ratio (e.g., inspiration-to-expiration ratio),inspiratory flow, expiratory flow, tidal volume, minute volume, apneaduration, breath sounds, rales, rhonchi, stridor, and changes in breathsounds such as decreased volume or change in airflow. In addition, insome cases the physiological monitoring system monitors otherphysiological sounds, such as heart rate to help with probe-offdetection, heart sounds (e.g., S1, S2, S3, S4, and murmurs), and changesin heart sounds such as normal to murmur or split heart soundsindicating fluid overload. Moreover, the physiological monitoring systemmay use a second probe over the chest for better heart sound detection,keep the user inputs to a minimum (for example, only input height), anduse a Health Level 7 (HL7) interface to automatically input demography.

A physiological monitoring system of certain embodiments includes one ormore patient monitoring devices connected to a shared network using openarchitecture communications standards. The patient monitoring devices ofcertain embodiments include a physiological monitor coupled with anetwork interface module. The physiological monitor includes one or moresensors and a sensor processing module for processing signals from thesensors. The network interface module receives physiological informationfrom the sensor processing module and transmits this information overthe shared network. The network interface module may connect to avariety of physiological monitors. In addition, the network interfacemodule of various implementations is a portable bedside device assignedexclusively to one medical patient.

In certain embodiments, the network interface module facilitatesestablishing a network connection directly with end users over theshared network. These end users, including doctors, nurses, and otherhospital staff, may receive physiological information, alarms, andalerts from the network interface module on an electronic device, suchas a pager, PDA, laptop, computer, computer on wheels (COW), or thelike.

Referring to FIG. 1, certain embodiments of a physiological monitoringsystem 100 (e.g., alarm notification system) include an open networkarchitecture using “off-the-shelf” hardware and communication protocols.This architecture in various implementations is a shared, or open,network includes multiple patient monitoring devices 110, a network bus120 (e.g., an Ethernet backbone), and a hospital WLAN 126. In addition,the shared network may further include a connection 122 to the Internet150, to end user devices 152 over the Internet 150, and to end userdevices 128 over the hospital WLAN 126. The physiological monitoringsystem 100 of certain embodiments is therefore an enterprise system thatachieves a cost-effective replacement for currently available patientmonitoring systems.

The physiological monitoring system 100 includes a plurality of bedsidedevices, e.g., patient monitoring devices 110. The patient monitoringdevices 110 of various embodiments include sensors 102, one or moresensor processing modules 104, and a communications module, e.g.,network interface module 106. In the depicted embodiment, two patientmonitoring devices 110 are shown. One patient monitoring device includesone set of sensors 102, one sensor processing module 104, and onenetwork interface module 106. The other patient monitoring device 110includes two sets of sensors 102, two sensor processing modules 104, andone network interface module 106.

In certain embodiments, each patient monitoring device 110 is used byone medical patient. The patient monitoring devices 110 form a networkof patient monitoring devices 110, each of which can communicate withclinicians and other end users over a shared network, including ahospital network 126 and network interfaces to the Internet 150.

One or more sensors 102 of the patient monitoring device 110 areattached to a medical patient. These sensors 102 may include ECGsensors, acoustic sensors, pulse oximeters, and other types of sensors.The sensors 102 obtain physiological information from a medical patientand transmit this information to the sensor processing module 104through cables 103 or through a wireless connection (not shown). Incertain embodiments, the physiological information includes one or morephysiological parameters or values and waveforms corresponding to thephysiological parameters.

The sensor processing module 104 receives physiological information fromthe sensors 102. The sensor processing module 104 of certain embodimentsincludes a circuit having a processor, input ports for receiving thephysiological information, software for processing the physiologicalinformation in the processor, an optional display, and optionally aninput device (e.g., a keyboard). In addition, the sensor processingmodule 104 contains one or more output ports, such as serial ports. Forexample, an RS232, RS423, or autobaud RS232 (serial interface standard)port or a universal serial bus (USB) port may be included in the sensorprocessing module 104.

In certain embodiments, the sensor processing module 104 generateswaveforms from signals received from the sensors 102. The sensorprocessing module 104 may also analyze single or multiparameter trendsto provide early warning alerts to clinicians prior to an alarm event.In addition, the sensor processing module 104 in certain embodimentsgenerates alarms in response to physiological parameters exceedingcertain safe thresholds.

Example alerts include no communication with pulse oximeter, alarmsilenced on pulse oximeter, instrument low battery (pulse oximeter), andtransmitter low battery. Example alarms include SpO₂ levels and alarms,high and low SpO₂, high and low PR, HbCO level and alarms, HbMET leveland alarms, pulse rate and alarms, no sensor, sensor off patient, sensorerror, low perfusion index, low signal quality, HbCO, HbMET, PI trendalarm, and desat index alarm.

The network interface module 106 in the depicted embodiment is connectedto one or more sensor processing modules 104 through one or moreconnectors 108, which may be serial connectors corresponding to theserial ports in the sensor processing modules 104. Dashed lines on theconnector 108 indicate that the network interface module 106 of certainembodiments is not permanently attached to the sensor processing modules104. In alternative embodiments (not shown), however, the networkinterface module 106 is contained within a sensor processing module 104.

The network interface module 106 in various implementations includes aprocessor, an input port (such as a standard RS232 serial port), anetwork output port such as an Ethernet port, and software which enablesthe network interface module 106 to act as a network-communicationsenabled device. In addition, the network interface module 106 includes astorage device 114, which may be included within the network interfacemodule 106 or attached separately to the network interface module 106.

The network interface module 106 manages the connectivity overhead forinitiating and maintain connectivity with end user devices over theshared network. In certain embodiments, the network interface module 106manages connectivity by acting as a microserver or web server. In suchinstances, the network interface module 106 is a network connectionenabled device. As a web server, the network interface module 106establishes direct connections to the Internet 150, such that an enduser may access web pages stored on the storage device 114 of thenetwork interface module 106. In one embodiment, the network interfacemodule 106 therefore does not require a separate server for connectingto the Internet 150. In one embodiment, the network interface module 106connects to the Internet 150 directly through a modem, such that theconnection 122 includes a modem. In managing connectivity over theshared network, the network interface module 106 may also performsecurity management functions, such as user authentication.

In certain embodiments, the network interface module 106 sends data overthe shared network through an access point 124 or other wireless orwired transmitter. Alternatively, the network interface module 106 maycommunicate physiological information directly to end users over theInternet 150. End users such as clinicians carrying notifier devices,e.g., end user devices 128, 152 connected to the hospital WLAN 126 mayreceive real-time viewing of physiological patient parameters andwaveforms on demand or in the event of an alarm or alert. Real-time orslightly delayed transmission of physiological information in certainembodiments comports with standards for alarm latency in compliance withJoint Commission on Accreditation of Healthcare Organizations (JCAHO)standards for effective alarm response. The network interface module 106of certain embodiments therefore adds functionality equivalent to acentral nurses' station.

In certain embodiments, the network interface module 106 performscontext management. In one embodiment, context management includesassociating context information with physiological information to form acontextual data package. Context information may include severalcategories of information, including the categories of contextinformation related to the network interface module 106, contextinformation related to the medical patient, context information relatedto usage of the network interface module 106, and context informationrelated to a network connection. Within one or more of these contextcategories, context information might include a patient name, apatients' unique hospital identification number, patient location, anidentification number for a network interface module 106, time stampsfor events occurring in the physiological monitoring system 100,environmental conditions such as changes to the state of the network andusage statistics of the network interface module 106, and identificationinformation corresponding to the network link (e.g., whether the networkconnection is WiFi or Ethernet). In one embodiment, the contextinformation in the contextual data package may include all of or anysubset of context information from one or more of the contextcategories.

The network interface module 106 receives context information, forexample, by a nurse entering the information in the network interfacemodule 106 or from a server 136. In one embodiment, by receiving thisinformation (including, e.g., patient identification number andlocation), the network interface module 106 becomes exclusively assignedto the medical patient. The network interface module 106 transmits orcommunicates the contextual data package to clinicians during an alarmor alert, upon clinician request, or on a scheduled basis. In addition,the network interface module 106 may transmit a continuous stream ofphysiological information to clinicians.

By optionally connecting to multiple sensor processing modules 104 incertain embodiments, the network interface module 106 is able toassociate patient context information and other context information withmultiple sensor processing modules 104. Consequently, context can becreated for one or more sensor processing modules 104 in addition tocontext being created for the network interface module 106.

In addition to transmitting the contextual data package, the networkinterface module 106 in one embodiment stores the contextual datapackage in the storage device 114. The storage device 114 may be a flashmemory, a hard disk drive, or other form of non-volatile or volatilememory. In certain embodiments the storage device 114 acts as a flowcontrol buffer. The network interface module 106 uses the storage device114 acting as a flow control buffer to perform flow control duringcommunications, as explained more fully below in connection with FIG. 3.

In some implementations, a server 136 may optionally be included in thephysiological monitoring system 100. The server 136 in theseimplementations is generally a computing device such as a blade serveror the like. In certain embodiments, the server 136 is an applianceserver housed in a data closet. In other embodiments, the server 136 isa server located at a central nurses' station, such as a workstationserver.

The server 136 receives contextual data packages from a plurality ofnetwork interface modules 106 and stores the contextual data package ina storage device 138. In certain embodiments, this storage device 138therefore archives long-term patient data. This patient data may bemaintained even after the patient is discharged. In storing patientdata, the server 136 may act as an interface between the shared networkand an external electronic medical record (EMR) system.

The server 136 may also store data concerning user interactions with thesystem and system performance metrics. Integrated into the server 136 ofcertain embodiments is a journal database that stores every alert andalarm or a subset of the alerts and alarms as well as human interactionin much the same way as an aviation “black box” records cockpitactivity. The journal is not normally accessible to the clinical enduser and, without technical authorization, cannot be tampered with. Inaddition, the server 136 may perform internal journaling of systemperformance metrics such as overall system uptime.

In one embodiment, the journaling function of the server 136 constitutesa transaction-based architecture. Certain transactions of thephysiological monitoring system 100 are journaled such that a timelineof recorded events may later be re-constructed to evaluate the qualityof healthcare given. These transactions include state changes relatingto physiological information from the patient monitoring devices 100, tothe patient monitoring devices 110, to the hospital WLAN 126 connection,to user operation, and to system behavior. Journaling related to thephysiological information received from a physiological monitor in oneembodiment includes recording the physiological information itself,recording changes in the physiological information, or both.

The server 136 in certain embodiments provides logic and managementtools to maintain connectivity between network interface modules 106,clinician notification devices such as PDAs and pagers, and externalsystems such as EMRs. The server 136 of certain embodiments alsoprovides a web based interface to allow installation (provisioning) ofsoftware rated to the physiological monitoring system 100, adding newdevices to the system, assigning notifiers (e.g., PDAs, pagers, and thelike) to individual clinicians for alarm notification at beginning andend of shift, escalation algorithms in cases where a primary caregiverdoes not respond to an alarm, interfaces to provide management reportingon the alarm occurrence and response time, location management, andinternal journaling of system performance metrics such as overall systemuptime (see, e.g., FIG. 5 and accompanying description).

The server 136 in certain embodiments also provides a platform foradvanced rules engines and signal processing algorithms that provideearly alerts in anticipation of a clinical alarm. The operating systemon the server 136 in one embodiment is Linux-based for cost reasons,though a Microsoft-based or other operating system may also be used.Moreover, the server 136 is expandable to include data storage devicesand system redundancy capabilities such as RAID (random array ofindependent disks) and High Availability options.

In another embodiment (not shown), end user devices 128, 152 include oneway POCSAG Pagers having a 2 line display with audible and vibrate mode,of suitable size and durability for severe mechanical environmentstypical of hospital general floor settings. In yet another embodiment,the end user devices 128, 152 include two way paging systems, such asMotorola Flex and WLAN pagers. One advantage of two-way paging is theability to confirm message receipt and the ability to remotely silencealarms. Wireless PDAs may also be used by end users based on ruggednessand acceptable form factors as determined by an end user. An example ofsuch a device is the Symbol Technology MC50 PDA/Barcode Scanner.

FIG. 2 depicts another embodiment of the physiological monitoring system200 of the present invention. The physiological monitoring system 200includes network communications enabled devices 210. The networkcommunications enabled devices 210 are connected directly to a hospitalnetwork 220 through a wireless connection. In certain embodiments, thenetwork communications enabled devices 210 include sensors and sensorprocessing modules, similar to the sensors 102 and sensor processingmodules 104 of FIG. 1. Certain of these network communications enableddevices 210 are bedside devices, and others are handheld or otherwisepatient-worn devices that may be used by an ambulatory (mobile) patient.

The hospital network 220 transmits physiological information and contextinformation to clinician notifier devices, including pagers 240, PDAs230, and the like. In certain embodiments, the hospital network 220utilizes a server 250 to transmit contextual data packages to a pagetransmitter 242, which further transmits the data to one-way wirelesspagers 240. An external interface 280 may be coupled with the server250. The external interface 280 could include one or more of thefollowing: enterprise paging, nurse call systems, wide area pagingsystems, enterprise clinical and patient information systems, and thirdparty monitoring and surveillance systems.

Certain other devices 260, such as some patient monitoring equipment,are not network communications enabled devices. That is, these otherdevices 260 are unable to connect to a network unaided. In the depictedphysiological monitoring system 200, example devices 260 that are notnetwork communications enabled are connected to a network interfacemodule 270. The network interface module 270 is connected to thenon-network communication enabled other devices 260 through RS232 cables264. Such a connection is a standardized serial connection found on manydevices. Because the network interface module 270 has an RS232 port, thenetwork interface module 270 can allow non-network communication enabledpatient monitoring devices to connect directly to the hospital network220 and also to the Internet.

Moreover, by connecting to one or more other devices 260 in someembodiments, the network interface module 270 is able to associatepatient context information and other context information with one ormore other devices 260. Consequently, context can be created for one ormore other devices 260 in addition to context being created for thenetwork interface module 270.

FIG. 3 depicts a network interface module 300 in accordance with certainembodiments of the present invention. The network interface module 300in the depicted embodiment includes an input port 302, which in certainembodiments is a serial port for facilitating a connection to a sensorprocessing module. The network interface module 300 also includes anetwork interface 304, which may be a wired interface (e.g., Ethernet)or a wireless interface such as WiFi, Bluetooth, or the like.Alternatively, the network interface module 104 may communicate througha cable TV interface or other type of interface. Such a CTV interfaceprovides a subcarrier bi-directional communications capability thatwould simultaneously co-exist with video formats.

The network interface module 300 also communicates with a storage device350. While in the depicted embodiment the storage device 350 is shown asseparate from the network interface module 300, in some implementationsthe storage device 350 is part of the network interface module 300. Inaddition, though not shown, the network interface module 300 may includea processor for implementing communications program code. Similarly,though not shown, the network interface module 300 may include an inputdevice for a nurse to input context information and a display forreceiving output from the network interface module 300.

The network interface module 300 can be integrated into handheld,portable or stationary patient monitoring platforms or instruments orcontained in an accessory package with an RS 232 input for generalinterface to such devices. In another embodiment, (not shown) activeRFID tag capabilities are included with the network interface module106, with the clinician devices (e.g., notifier devices), or with bothso that either a patient or a clinician can be located when an eventoccurs or on request. When operating on a shared network, the networkinterface module 106 is also compliant with to the open architecturecommunications standards of IEEE 802.1X (security and authorization),IEEE 802.3 (Ethernet), and WiFi (IEEE 802.11 a, b, g, e, i wirelessprotocols).

A context management module 310 in the network interface module 300manages context data. In one embodiment, the context management module310 receives context information, such as the context informationdescribed in connection with FIG. 1 above. In one embodiment, a nurse orother clinician enters context information, such as patient name,identification number, and location, into the network interface module300 via a keyboard or other input device (not shown) when the patient isadmitted to the hospital or assigned a particular bed in the hospital.In other embodiments, the context management module 310 receives thecontext information from a server, such as the server 136 of FIG. 1.

The context management module 310 associates the context informationwith physiological information received from a sensor processing module.In certain embodiments, the context management module 310 performs thisassociation when an alarm condition occurs. In such instances, thecontext management module 310 may create a contextual data packageincluding a snapshot of historical physiological information togetherwith the context information. In other embodiments, the contextmanagement module 310 performs an association continuously, and thenetwork interface module 300 sends continuous or scheduled contextualdata packages to end users. In addition, the context management module310 or other modules in the network interface module 300 store thecontextual data package in the storage device 350.

The communications module 320 uses the network interface 304 tocommunicate with a network. In certain embodiments, the communicationsmodule 320 possesses the functionality of a web server. As a web server,the communications module 320 enables the network interface module 300to communicate with a hospital network and the Internet directly,without using a server. Consequently, other devices such asphysiological monitoring devices that are not network connection enabledmay connect with the network interface module and thereby become networkenabled. The network interface module 300 manages the connectivityoverhead for initiating and maintaining connectivity, manages contextinformation (e.g., any of the context information described above inconnection with FIG. 1), and provides a web server for displayingpatient information on web-enabled devices. In one embodiment, acommunications protocol based on XML technologies allows bedside devicesto interface to a multitude of target end user platforms including PDAs,computer on wheels (COW), Tablet PCs, IP cell phones (smartphones), andfixed PCs.

In certain embodiments, the communications module 320 uses standardcommunications protocols to communicate with a network. Some examples ofstandard communications protocols include Ethernet, WiFi (WLAN),Bluetooth, and the like. By using standard communications protocols, thecommunications module 320 is able to send and receive data over a sharednetwork or open network architecture. However, the communications module320 may also be used on a proprietary network using proprietaryprotocols.

In embodiments where the network interface module 300 communicates overa shared network rather than a proprietary network, the networkinterface module 300 shares network resources with other devices on thenetwork. In some cases, high-volume network traffic affects thereliability of network communications. Consequently, certainimplementations of the network interface module 300 include a flowcontrol module 330. The flow control module 330 verifies thattransmitted data was received by an end user. In the event that the enduser did not receive the data, the flow control module 330 resends thedata stored in the storage device 350. In certain embodiments, thestorage device 350 therefore acts as a flow control buffer.

A security module 340 manages user access to the network interfacedevice 300 and to data stored in the storage device 350. In certainembodiments, the security module 340 determines whether a userattempting to connect to the network interface module 300 is authorizedto do so. In one implementation, the security module 340 uses thestandard IEEE.802.1X network access control protocol to manageauthentication. The network interface module 106 in certain embodimentsprovides security and encryption to meet the Health InsurancePortability and Accountability Act (HIPAA) requirements.

In certain embodiments, the network interface module 300 incorporatesall or a portion of the functionality specified by the IEEE 1073standard and the most recent update to the IEEE 1073 standard, namelythe IEEE 11703 standard, both of which are hereby incorporated byreference. In certain embodiments, the context management module 310,the communications module 320, the flow control module 330, and thesecurity module 340 also incorporate functionality specified in the IEEE1073 and 11703 standards. By using standard protocols, the networkinterface module 300 may be used to enable network communication for awide variety of physiological monitoring devices.

FIG. 4 depicts a process 400 for context-based communication ofphysiological information according to an embodiment of the presentinvention. In certain embodiments, the process 400 is performed by anyof the network interface modules described above in connection withFIGS. 1-3. In addition, the process 400 in certain embodiments may beperformed by any of the physiological monitoring systems described inconnection with FIGS. 1, 2, and 5.

The process 400 begins by receiving context information at 402. In oneembodiment, a device such as a network interface module receives thecontext information once, such as in an initialization step. The process400 then receives physiological information at 404. In certainembodiments, the process 400 continues to receive physiologicalinformation throughout the remaining steps of the process 400.Alternatively, the process 400 may receive physiological information 400for a portion of the process 400.

At 405, the process 400 determines whether an alarm condition or alerthas occurred. If an alarm condition or alert has occurred, the process400 proceeds to 406. However, if an alarm condition or alert has notoccurred, the process 400 loops back to 404. In one embodiment, thelooping back of the process 400 to 404 represents that a networkinterface module continually receives physiological information until analarm condition or alert occurs. In certain embodiments (not shown), theprocess 400 may continue to receive physiological information even whenan alarm condition or alert occurs.

At 406 the process 400 prepares a contextual data package. Thecontextual data package may include context information and a snapshotof physiological information. In one embodiment, the snapshot ofphysiological information includes the physiological information thatgave rise to an alarm or alert. In one embodiment, the snapshot ofphysiological information includes information both before and after theoccurrence of an alarm or alert. The contextual data package is storedin a flow control buffer at 408.

At 410, the process 400 establishes a network connection. In oneembodiment, establishing a network connection at 410 includes connectinga network interface module to an end user device, such as a notifierdevice assigned to a nurse during his or her work shift. The process 400then determines at 412 whether the user of the device (e.g., the nurse)has been authenticated. If the user has not been authenticated, theprocess 400 proceeds to 420. On the other hand, if the user has beenauthenticated, the process 400 proceeds to 414.

The process 400 at 414 communicates the contextual data package to theuser. At 416, the process 400 determines whether the contextual datapackage was received. If the contextual data package was received, theprocess 400 proceeds to 420. Otherwise, the process 400 proceeds to 418,where the process 400 accesses data stored in the flow control buffer.In one embodiment, the data accessed by the process 400 is equivalent toor substantially equivalent to the contextual data package communicatedto the user at 414.

The process 400 then loops back to 414, where the process 400communicates (e.g., resends) the contextual data package to the user,and then at 416 re-verifies that the package was received. The process400 in some implementations continues to loop between steps 414, 416,and 418 until the contextual data package was received. Thus, steps 414,416, and 418 in certain embodiments constitute flow control performed bythe process 400. These flow control steps allow the process 400 toovercome network transmission errors which may occur in shared networks.

If the contextual data package was received, the process 400 evaluateswhether to continue the monitoring of physiological information at 420.If the process 400 determines to continue monitoring, the process loopsback to 404, where the process 400 continues to receive physiologicalinformation. If, however, the process 400 determines not to continuemonitoring, the process 400 ends.

In various embodiments of the process 400, the contextual data packageor the physiological information alone is transmitted to the user evenin the absence of an alarm condition. In still other embodiments, fewerthan all of the steps are performed, or the steps are performed indifferent order. For instance, the process 400 may only perform thesteps of receiving physiological information at 404, preparing acontextual data package at 406, establishing a network connection at410, and communicating the contextual data package to the user at 414.

FIG. 5 depicts an alarm notification system 500 in accordance withcertain embodiments of the present invention. A clinical subsystem 510defines the major software components of alarm notification system 500including a clinical assignment module 512, a bedside deviceinitialization module 514, a notification and viewing module 516, anescalation rules module 518, a clinical report module 520, and aclinical data stores module 522. An authentication feature is built intomobile computing devices in compliance with HIPAA and hospital ITpolicies.

The clinical assignment module 512 has an assignment function. A nursingsupervisor assigns individual nurses to specific patients at the startof each shift and upon admission of new patients. Shift assignments takeplace at change of shift during a “report” transition exercise whereindividual nurses and nursing supervisor from previous shift “hand off”patients to the next shift. The report can be either formal where allnurses attend or informal dependent on hospital nursing service policiesand procedures. The clinical assignment module 512 provides an intuitiveinterface that allows a listing of available nurses to be assignedindividual patients. The major user of this module is the unit clerk asassigned by the nursing supervisor. A nurse can be assigned one or morepatients or all patients. An alternative work flow is self assignmentwhere individual nurses assign patients themselves in which case theyperform functions of the unit clerk. In the self assignment model, adefault is implemented where any unassigned patient is either assignedto all nurses or the nursing supervisor.

The bedside device initialization module 514 has bedside devices, suchas the network interface modules described above, that are sometimes setup by an aide to the nurse. In the case where the nurse performs thistask, she or he performs the functions of the nursing aide. Work flowincludes delivering a device to bedside, applying sensors, initializingthe device, and setting patient context, such as name, ID and location.

The notification and viewing module 516 assigns a wireless notificationdevice, such as a one-way pager, PDA, IP telephone, COW, or Tablet toindividual nurses. The device becomes associated with her or him. Alarmsare routed to the notification device based on the clinical assignmentmodule 512. Non-dedicated notifier solutions such as hospital ownedpaging systems issued to nurses have unknown latency characteristics. Ageneral purpose interface is available at the server with a latency ofless than 1 second upon receipt from the bedside device and is timestamped upon presentation to the server external interface and stored ina journaling system within the server. An additional interface formobile computing platforms such as PDA, COWS, and Tablets allows viewingof current and trend data for an individual patient.

The escalation rules module 518 has a rules engine that actuates anescalation policy defined by the hospital. The escalation rules module518 provides alternative routing of alarms to alternative and additionalclinical users in the event an alarm is not responded to or persists fora predefined (e.g., by a policy) period of time. The escalation rulesmodule 518 in certain embodiments routes alarms to an emergency responseteam.

The clinical report module 520 provides predefined formatted reports onthe clinical data from which to determine physiologic condition and/orprogress. More than one report may be dependent on end user needs.Reports are not time critical views of individual patients and may beremotely viewed by clinicians who have alarm notification system 500privileges and have been authenticated by the alarm notification system500. These reports are web browser views that allow clinicians to setviewing parameters such as time and parameter scales and alarm review.

The clinical data stores module 522 provides data storage and databaseresources to store information as known to those skilled in the art.

Further shown in FIG. 5, a technical support subsystem 530 is isolatedfrom the clinical subsystem 510 in compliance with HIPAA and as suchdoes not allow viewing or access to any patient information with theexception of the risk report module 538. The technical support subsystem530 includes a provisioning module 532, an administration module, aservice module 536, a risk report module 538, and a technical data storemodule 540.

The provisioning module 532 provides provisioning, which is the initialinstallation of the system and first customer use. The primary user ofthe provisioning module 532 is the field installer. The provisioningmodule 532 contains all the start up scripts and system configurationsto bring the system from shipping boxes to full alarm notificationsystem 500 functionality. Provisioning includes steps to configureindividual devices, notifiers such as pagers, PDA, COW, Tables and IPtelephone at the customer site, preferably by wireless means (e.g.,Bluetooth).

The administrative module 534 provides a system interface for theapplication administrator to set up users, set policies for variousactor privileges such as a nurses aide being able to set or changealarms, set up allowed device connection identifications, and othergeneral systems administrative duties typical of IT systems.

The service module 536 provides interfaces for various technical supportactors including remote service, IT Service, and Biomed Service. Each ofthese actors may perform each others' functions. Interfaces allow theservice actors to access system performance data to access performance,for example, data traffic, device assets connected, software versionmanagement, CPU loading, network loading, etc. and execute remotetechnical service procedures, for example, resetting a printer queue,repartition of disk, uploading software patches, etc. The service module536 includes a full journaling function that stores every userinteraction or a portion of user actions that can be captured by thesystem, especially changes in default values or alarm settings.

The risk report module 538 provides summary reports on alarmoccurrences, duration of alarm, clinical response time to alarms andother statistical data to determine overall effectiveness of clinicalresponse to alarms in compliance with JCAHO, other regulatory bodies,and internal quality assurance committees.

The technical data stores module 540 has the same characteristics as theclinical data stores module 522 except that the technical data storesmodule 540 is used for technical data. The technical data stores module540 may or may not share the same physical and logical entity as theclinical data stores module 522.

Additionally shown in FIG. 5, an external interface subsystem 550provides interfaces to bedside devices and external systems such aselectronic medical records, admit discharge, transfer systems, POCSAGpager systems, middleware engines such as Emergin, and Web/XML enableddevices such as wireless PDAs, COWs and Tablet PCs. The externalinterface subsystem 550 has an HL7 interface 552, a pager interface 554,an XML/Web interface 556, and a device interface 558.

The HL7 interface 552 provides a bi-directional interface to electronicmedical records (EMR) and supports both push and pull models. The pushmodel is when a bedside nurse initiates data transfer. The pull model iswhen an EMR system polls the alarm notification system 500 server. Thepager interface 554 provides output to external paging system. Messagelatency is identified to an end user for any user-owned paging solution.This same output can be used for middleware alarm notification systemssuch as Emergin. The XML/Web interface 556 provides bi-directionalinterface with mobile computing platforms such as wireless PDA, COWs,Tables, and Web-enabled IP phones. Mobile computing platforms supportWeb Browser XML applications. The device interface 558 provides abi-directional interface to bedside devices as well as to other devicesenabled by the communications module or accessory. ApplicationProgrammer Interface (API) capability is an option for interfacing toother bedside devices.

The major end users of the alarm notification system 500 system (notshown or described for simplicity) include hospital electronic medicalrecords, admit discharge transfer, pharmacy, clinical information,patient flow tracking and others. Actors, e.g., users of the alarmnotification system 500, including clinical actors and technical supportactors. The clinical actors include nursing supervisors, unit clerks,nursing aides, nurses, rapid response teams and respiratory therapists.

A nursing supervisor assigns individual nurses to specific patients atthe beginning of each shift. Shift can vary according to hospitalstaffing policies. A unit clerk takes direction from the nursingsupervisor, typically inputs assignments into system and monitorsoverall system. A unit clerk may not be available for all shifts. Anursing aide takes assignments from nurse or nursing supervisor,typically applies bedside device sensor, initializes the bedside deviceand sets alarms to default values. A nurse has primary responsibilityfor individual patient care and primary response to alarms. The nurse isassigned by nursing supervisor to more than one patient dependent onher/his skills and patient needs and is not always assigned the samepatient. Nursing aides are not found in all hospitals.

A rapid response team responds to clinical emergencies initiated byeither a bedside nurse or a nursing supervisor. The team supports morethan one care unit and has one or more members depending on shift. RapidResponse Teams may not be implemented in all hospitals. A respiratorytherapist has responsibilities for management of respiratory care formore than one patient and usually more than one care unit. Respiratorytherapists are not found in some international settings.

Clinical actor performance substitution allows a high capability actorto assume the roles of other actors. Alarm notification system 500allows mechanisms for such performance. For example, a nursingsupervisor may perform functions of a unit clerk nursing aide, a nurseand a rapid response team. A nurse may perform functions of a unitclerk, a nursing aide and a rapid response team. In some internationalmarkets a nurse may perform the functions of a respiratory therapist.

The technical support actors include field installers, applicationadministrators, remote services, IT engineers, biomedical engineers andrisk managers. A field installer provisions the system for initialinstallation, installs components, and validates that the installationand configuration meet a purchasing contract. An applicationadministrator sets up and maintains user accounts and systems defaults.A remote service provides remote diagnostics and system maintenance overa remote link, such as dial up and VPN. An IT engineer provides networksupport services if the system is integrated with the hospital ITnetwork. A biomedical engineer provides bedside and system primaryservice. A risk manager reviews reports for quality and risk mitigationpurposes. Technical support actors may also fill in for other actors.For example, an IT engineer, a biomedical engineer, or a remote servicecan perform the functions of an application administrator. An ITengineer or a biomedical engineer can perform each other's functions.

In certain embodiments, systems and methods are provided for rapidlystoring and acquiring physiological trend data. For instance,physiological information obtained from a medical patient can be storedin a round-robin database. The round-robin database can store thephysiological information in a series of records equally spaced in time.Parameter descriptors may be used to identify parameter values in therecords. The parameter values can be dynamically updated by changing theparameter descriptors to provide for a flexible database. In addition,the size of files used in the database can be dynamically adjusted toaccount for patient condition.

Additionally, in certain embodiments, medical data obtained from aclinical network of physiological monitors can be stored or journaled ina journal database. The medical data can include device events thatoccurred in response to clinician interactions with one or more medicaldevices. The medical event data may also include device-initiatedevents, such as alarms and the like. The medical data stored in thejournal database can be analyzed to derive statistics or metrics, whichmay be used to improve clinician and/or hospital performance.

As used herein the terms “round-robin database” and “RRDB,” in additionto having their ordinary meaning, can also describe improved databasestructures having unique characteristics and features disclosed herein.Sometimes these structures are referred to herein as dynamic RRDBs oradaptive RRDBs.

FIG. 6 illustrates an embodiment of a clinical network environment 600.The clinical network environment 600 includes a multi-patient monitoringsystem (MMS) 620 in communication with one or more patient monitors 640,nurses' station systems 630, and clinician devices 650 over a network610. In certain embodiments, the MMS 620 provides physiological dataobtained from the patient monitors 640 to the nurses' station systems630 and/or the clinician devices 650. Additionally, in certainembodiments, the MMS 620 stores physiological information and medicalevent information for later analysis.

The network 610 of the clinical network environment 600 can be a LAN orWAN, wireless LAN (“WLAN”), or other type of network used in anyhospital, nursing home, patient care center, or other clinical location.For ease of illustration, the remainder of this specification willdescribe clinical environments in the context of hospitals; however, itshould be understood that the features described herein may also beemployed in other clinical locations or settings. In someimplementations, the network 610 can interconnect devices from multiplehospitals or clinical locations, which may be remote from one another,through the Internet, a leased line, or the like. Likewise, the variousdevices 620, 630, 640, and 650 of the clinical network environment 100may be geographically distributed (e.g., among multiple hospitals) orco-located (e.g., in a single hospital).

The patient monitors 640 may be point-of-care (POC) instruments or thelike that monitor physiological signals detected by sensors coupled withmedical patients. The patient monitors 640 may process the signals todetermine any of a variety of physiological parameters. One example of aphysiological parameter is blood oxygen saturation (SpO₂). Otherexamples of physiological parameters are described below with respect toFIG. 7.

The patient monitors 640 can provide the physiological information tothe MMS 620. The patient monitors 640 can also provide information onmedical events, such as alarms, to the MMS 620. Alarms can be triggered,for example, in response to a physiological parameter falling outside ofa normal range. Alarms can also include alerts regarding equipmentfailures, such as a probe-off condition where a sensor has fallen off ofa patient. Other examples of medical events are described below withrespect to FIG. 7.

In various embodiments, the patient monitors 640 provide thephysiological information and medical events to the MMS 620. The MMS 620is described in greater detail below. In some implementations, thepatient monitors 640 may provide at least some of this informationdirectly to the nurses' station systems 630 and clinician devices 650.

The nurses' station systems 630 can be desktop computers, laptops, workstations, or the like that are located at a nurses' station. One or morenurses' station computers 630 can be located at a single nurses'station. The nurses' station computers 630 can receive and displayphysiological information and alarm data received from the MMS 620 (ormonitors 640). In certain embodiments, the nurses' station computers 630use a graphical user interface (GUI) that provides a streamlined,at-a-glance view of physiological and medical information. An example ofthis GUI is described below with respect to FIG. 9.

The clinician devices 650 can include any of a variety of devices usedby clinicians, such as pagers, cell phones, smart phones, personaldigital assistants (PDA), laptops, tablet PCs, personal computers, andthe like. The clinician devices 650 are able to receive, in someembodiments, physiological information and alarms from the MMS 620 (ormonitors 640). Physiological and alarm data can be provided to aparticular clinician device 650, for example, in response to an alarm.The clinician devices 650 can, in some instances, receive values andwaveforms of physiological parameters.

The MMS 620 in certain embodiments includes one or more physicalcomputing devices, such as servers, having hardware and/or software formanaging network traffic in the network 610. This hardware and/orsoftware may be logically and/or physically divided into differentservers 620 for different functions, such as communications servers, webservers, database servers, application servers, file servers, proxyservers, and the like.

The MMS 620 can use standardized protocols (such as TCP/IP) orproprietary protocols to communicate with the patient monitors 640, thenurses' station computers 630, and the clinician devices 650. In oneembodiment, when a patient monitor 640 wishes to connect to the MMS 620,the MMS 620 can authenticate the patient monitor 640 and provide themonitor 640 with context information of a patient coupled to the monitor640. Context information can include patient demography, patient alarmsettings, and clinician assignments to the patient, among other things.Examples of context information are described herein. The MMS 620 mayobtain this context information from the nurses' station systems 630 orother hospital computer systems, where patient admitting information isprovided.

Upon connecting to a patient monitor 640, the MMS 620 may receivephysiological information and medical events from the patient monitors640. The MMS 620 may provide at least a portion of the physiologicalinformation and events to the nurses' station systems 630 and/orclinician devices 650. For example, the MMS 620 may providephysiological data and alarms for a plurality of patient monitors 640 toa nurses' station system 630, where nurses can evaluate the data and/oralarms to determine how to treat patients. Similarly, the MMS 620 maysend wireless pages, emails, instant messages, or the like to cliniciandevices 650 to provide clinicians with physiological data and alarms.

Advantageously, in certain embodiments, the MMS 620 can storephysiological information obtained from the patient monitors 640 in around-robin database (RRDB) 624. The RRDB 622 of various embodimentsincludes a streamlined database structure that facilitates rapidlystoring and retrieving patient data. The RRDB 622 can therefore be usedin certain embodiments to rapidly provide physiological trend data tothe nurses' stations 630 and to the clinician devices 650. Thus, forexample, if a clinician desires to see a patient's physiological trendsover a certain time period, such as the past hour, the clinician can usea nurses' station computer 630 or clinical device 650 to query the MMS620. The MMS 620 may then obtain physiological information correspondingto the desired time period from the RRDB 622. Advantageously, the RRDB622 can enable faster acquisition of trend data then is possible withrelational databases currently used by hospital monitoring systems.Additional uses and optimizations of the RRDB 622 are described below.

In certain embodiments, the MMS 620 also archives or stores informationabout medical events in a journal database 624. The medical events caninclude events recorded by devices such as the patient monitors 640,nurses' station systems 630, and clinician devices 650. In particular,the medical events can include device events that occur in response to aclinician's interaction with a device, such as a clinician-initiateddeactivation of an alarm. The medical events can also include deviceevents that occur without a clinician's interaction with the device,such as the alarm itself. Additional examples of medical events aredescribed below with respect to FIG. 7.

The MMS 620 may analyze the medical event information stored in thejournal database 624 to derive statistics about the medical events. Forexample, the MMS 620 can analyze alarm events and alarm deactivationevents to determine clinician response times to alarms. Using thesestatistics, the MMS 620 may generate reports about clinician and and/orhospital performance. Advantageously, in certain embodiments, thesestatistics and reports may be used to improve the performance ofclinicians and hospitals.

For instance, in certain situations, the reports might help hospitalsdiscover the cause of issues with patient monitors 640. The followingexample scenario can illustrate potential benefits of such a report.SpO₂ alarm levels tend to be different for adults and neonates. However,some clinicians may not know this and may modify neonate SpO₂ monitorsto include adult alarm levels. These changes can result in many falsealarms, which may cause clinicians to become frustrated and avoid usingthe patient monitors 640. By journaling medical events such as clinicianalarm changes, it can be determined by an analysis of the journaled datathat clinicians were inappropriately adjusting alarm settings on neonatemonitors. A hospital could then use this information to take correctiveaction, such as by fixing the alarm limits and training the clinicians.

Although not shown, administrative devices may be provided in theclinical network environment 600. The administrative devices can includecomputing devices operated by hospital administrators, IT staff, or thelike. Using the administrative devices, IT staff may, for example,promulgate changes to a plurality of patient monitors 640, nurses'station systems 630, and the MMS 620. The administrative devices mayalso allow IT staff to interface third-party systems with the MMS 620,such as electronic medical record (EMR) systems. The third party systemsmay be used, for instance, to change alarm settings on a plurality ofmonitors from an administrative device. Actions performed byadministrators, IT staff, and administrative devices in general may alsobe journaled in the journal database 624.

FIG. 7 illustrates a more detailed embodiment of a clinical networkenvironment 700. The clinical network environment 700 includes a network710, a patient monitor 740, a nurses' station system 730, an MMS 720, anRRDB 722, and a journal database 724. These components may include allthe functionality described above with respect to FIG. 6. One monitor740 and nurses' station system 730 are shown for ease of illustration.In addition, although not shown, the clinician devices 750 describedabove may also be included in the clinical network environment 700.

The depicted embodiment of the patient monitor 740 includes a monitoringmodule 742, an RRDB module 744, and a journal module 746. Each of thesemodules may include hardware and/or software. Other components, such asa communications module, are not shown but may be included in thepatient monitor 740 in various implementations.

The monitoring module 742 can monitor physiological signals generated byone or more sensors coupled with a patient. The monitoring module 742may process the signals to determine any of a variety of physiologicalparameters. For example, the monitoring module 742 can determinephysiological parameters such as pulse rate, plethysmograph waveformdata, perfusion index, and values of blood constituents in body tissue,including for example, arterial carbon monoxide saturation (“HbCO”),methemoglobin saturation (“HbMet”), total hemoglobin (“HbT” or “SpHb”),arterial oxygen saturation (“SpO₂”), fractional arterial oxygensaturation (“SpaO₂”), oxygen content (“CaO₂”), or the like.

In addition, the monitoring module 742 may obtain physiologicalinformation from acoustic sensors in order to determine respiratoryrate, inspiratory time, expiratory time, inspiration-to-expirationratio, inspiratory flow, expiratory flow, tidal volume, minute volume,apnea duration, breath sounds, rales, rhonchi, stridor, and changes inbreath sounds such as decreased volume or change in airflow. Inaddition, in some cases the monitoring module 742 monitors otherphysiological sounds, such as heart rate (e.g., to help with probe-offdetection), heart sounds (e.g., S1, S2, S3, S4, and murmurs), andchanges in heart sounds such as normal to murmur or split heart soundsindicating fluid overload. Moreover, the monitoring module 742 maymonitor a patient's electrical heart activity via electrocardiography(ECG) and numerous other physiological parameters.

In some implementations, the patient monitors 740 may also determinevarious measures of data confidence, such as the data confidenceindicators described in U.S. Pat. No. 7,024,233 entitled “Pulse oximetrydata confidence indicator,” the disclosure of which is herebyincorporated by reference in its entirety. The patient monitors 740 mayalso determine a perfusion index, such as the perfusion index describedin U.S. Pat. No. 7,292,883 entitled “Physiological assessment system,”the disclosure of which is hereby incorporated by reference in itsentirety. Moreover, the patient monitors 740 may determine aplethysmograph variability index (PVI), such as the PVI described inU.S. Publication No. 2008/0188760 entitled “Plethysmograph variabilityprocessor,” the disclosure of which is hereby incorporated by referencein its entirety. The parameters described herein are merely examples,and many other parameters may be used in certain embodiments.

In certain embodiments, the RRDB module 744 receives physiologicalinformation from the monitoring module 742 and transmits thephysiological information over the network 710 to the MMS 720. Inresponse, the MMS 220 may store the physiological information in theRRDB 722. Advantageously, in certain embodiments, the RRDB module 744associates the physiological information with parameter descriptorsprior to transmittal to the MMS 720. The parameter descriptors may beidentifiers that the RRDB module 744 associates with each measuredphysiological parameter value. The MMS 720 may use these parameterdescriptors to identify the types of measured parameters received fromthe RRDB module 744.

The parameter descriptors may be descriptors generated according to amarkup language specification, such as an extensible markup language(XML) specification. As such, the parameter descriptors may include tagsthat enclose measured physiological values. These tags may be machinereadable or human readable. For instance, the tags may include numericalidentifiers (e.g., “0017”) or descriptive identifiers, such as “SPO2” or“SPHB.” A simplified example stream of physiological information from anSpO₂ sensor and an SpHb sensor associated with parameter descriptorsmight be as follows: <SPO2>96</SPO2> <SPHB>14.1</SPHB> <SPO2>97</SPO2><SPHB>14.0</SPHB>, and so on.

In one embodiment, the RRDB module 744 may have stored (e.g., in a datafile) a set of predefined parameter descriptors available for thepatient monitor 740. These parameter descriptors may correspond topossible parameters that may be measured by the patient monitor 740. Theparameter descriptors transmitted by the RRDB module 744 may depend onthe particular subset of parameters measured by the patient monitor 740.

If an additional (or different) parameter is subsequently measured bythe patient monitor 740, the RRDB module 740 may dynamically update theparameter descriptors that are sent to the MMS 720. Likewise, if thepatient monitor 740 ceases to measure one of the parameters, the RRDBmodule 744 may cease to transmit the corresponding parameter descriptorto the MMS 720.

The patient monitor 740 also includes a journal module 746 in thedepicted embodiment. The journal module 740 may record medical eventsrelated to the patient monitor 740. These medical events can includeclinician-initiated events, such as changes to alarm settings (e.g.,maximum and minimum permitted parameter values), types of parametersmonitored/sensors connected to the patient monitor 740, and the like.The journal module 746 may record these events by, for example, actingas a key logger or the like to record button presses of a clinician. Thejournal module 746 may also include current-sense circuitry to detectwhen sensors or cables are connected to the monitor 740, and so forth.The medical events may also include non-clinician initiated events, suchas alarms and alerts. The medical events can also include events fromadministrative devices (not shown), such as EMR updates to alarmsettings across the network 710.

The journal module 746 may log these events locally at the patientmonitor 740. In addition, or instead of logging the events locally, thejournal module 746 may transmit information about the events to the MMS720. In turn, the MMS 720 can store the event information in the journaldatabase 724.

The nurses' station system 730 is shown in the depicted embodimenthaving a patient monitoring client 732. The patient monitoring client732 can enable the nurses' station system 730 to receive and displayphysiological information and alarm information. The patient monitoringclient 732 includes a user interface module 734. The user interfacemodule 734 may include, for example, software for displayingphysiological information, patient information, and medical eventinformation for a plurality of patient monitors 740. The user interfacemodule 734 may also allow clinicians to admit and discharge patients,remotely modify device alarm limits, and the like. An example userinterface that may be generated by the user interface module 734 isdescribed below with respect to FIG. 9.

The patient monitoring client 732 further includes a journal module 736.The journal module 736 may include software for recording medical eventsrelated to the patient monitoring client 732. For example, the journalmodule 736 may record which clinicians login to and logoff of thepatient monitoring client 732 and when these events occur; admit anddischarge events; and other clinician keystrokes, mouse clicks, andinteractions with the patient monitoring client 732. The journal module736 may log this event information locally at the nurse's station system730 and/or transmit the event information to the MMS 720.

As shown, the MMS 720 may include a network management module 721, anRRDB management module 723, and a journal management module 725, each ofwhich may include one or more software components. In one embodiment,the network management module 721 receives messages containingphysiological information and medical event data from the patientmonitor 740. The network management module 721 can provide at least aportion of this data to the nurses' station system 730 and cliniciandevices 650 of FIG. 6. The network management module 721 can alsoprovide the physiological information to the RRDB management module 723and provide the medical event data to the journal management module 725.

In certain embodiments, the RRDB management module 723 stores thephysiological information received from the patient monitor 740 in theRRDB 722. When the patient monitor 740 initially connects to the MMS720, or at another time, the RRDB management module 723 can create oneor more RRDB files in the RRDB 722 corresponding to the patient monitor740. The contents of this file or files may depend on the type ofpatient monitor 740, which may be defined by the patient monitor's 740serial number, model number, vendor identifier, combinations of thesame, or the like. Specific examples of the structure and contents ofRRDB files are described in US Patent Publication 2009/0119330, theentire contents of which are hereby incorporated by reference herein.

The RRDB management module 723 can also provide physiological trend datastored in the RRDB to the network management module 721 for transmittalto monitors 740, nurses' station systems 730, and/or clinician devices.The RRDB management module 723 may also provide physiological data fromthe RRDB 722 to the journal management module 725 for purposes describedbelow with respect to FIG. 8B.

The journal management module 725, in certain implementations, receivesmedical event data from the monitor 740 and the nurses' station system730 and stores this data in the journal database 724. In an embodiment,the journal database 724 is a relational database; however, otherstructures may be used. Each entry of event data may have acorresponding time stamp that indicates when an event occurred. Thistime stamp may be provided by the journal modules 746 or 736 or by thejournal management module 725. The journal management module 725 mayalso store event counters in the journal database 724 that reflect anumber of times medical events occurred. For example, counters could bestored that count how many alarms occurred within a period of time orhow many times a clinician logged on or logged off of a network device.

Advantageously, the journal management module 725 may, in certainembodiments, analyze the medical data in the journal database 724 todetermine statistics or metrics of clinician and/or hospitalperformance. The journal management module 725 may provide an interfaceto users of the nurses' station system 730 or another computing deviceto access these statistics. In one example embodiment, journalmanagement module 725 can analyze alarm events and alarm deactivationevents to determine clinician response times to alarms. The journalmanagement module 725 may further determine the clinician response timesin nurses' day and night shifts. The journal management module 725 maygenerate reports of these statistics so that hospital administrators,for example, may determine which shifts perform better than others.

More generally, the journal management module 725 may generate reportsabout clinician and and/or hospital performance by analyzing variousstatistics derived from data in the journal database 724. One example ofa report is a monitoring report card, which grades a given hospitalagainst other hospitals (or nurses' station against nurses' station, andthe like) based at least partly on the derived statistics.Advantageously, hospital administrators, clinicians, and the like mayuse these statistics and reports to improve the clinician and hospitalperformance.

Some or all of the features of the clinical network environment 700 maybe adapted in certain embodiments. For instance, either or both of thejournal modules 746 or 736 may perform some or all of the functions ofthe journal management module 725. Likewise, one or more journaldatabases 724 may be stored at the patient monitor 740 and/or nurses'work station 730. Similarly, the RRDB module 724 may perform some or allof the functions of the RRDB management module 723, and an RRDB 722 maybe stored at the patient monitor 740. In addition, in someimplementations, the clinician devices 650 of FIG. 6 may have RRDBand/or journal modules as well. Many other adaptations, configurations,and combinations may be made in other embodiments. Additionalinformation regarding embodiments of the RRDM can be found in US PatentPublication 2009/0119330.

FIG. 8A illustrates an embodiment of a process 800A for journalingmedical events in a journal database. In one embodiment, the process800A may be implemented by any of the MMS's described above (e.g., theMMS 620 or 720). In particular, the process 800A may be implemented bythe journal management module 725. Alternatively, at least some of theblocks may be implemented by the journal modules 736, 746.Advantageously, in certain embodiments, the process 800A facilitates thegeneration of reports based on the journaled data.

At block 802, medical events are journaled in a journal database. Inresponse to requests for report from a user (e.g., a clinician), atblock 804 statistics about the medical events are obtained from thejournal database. The statistics may include the type, frequency, andduration of medical events, the identity of clinicians or patientsassociated with the events, alarm response times, combinations of thesame, and the like.

A report is generated at block 806 regarding the medical eventstatistics. At block 808, the report is used to identify potential areasof improvement in hospital operations. For example, the report can be a“monitoring report card” that assigns scores to the hospital orclinicians of the hospital based on their performance.

FIG. 8B illustrates an embodiment of a process 800B for correlating datafrom a journal database and an RRDB. In one embodiment, the process 800Bmay be implemented by any of the MMS's described above (e.g., the MMS620 or 720). In particular, the process 800B may be implemented by theRRDB module 723 and journal management module 725. Alternatively, atleast some of the blocks may be implemented by the RRDB module 744 andjournal modules 736, 746. Advantageously, in certain embodiments, theprocess 800B enables physiological information from the RRDB and medicalevents to be correlated in time. Such a reconstruction of events andphysiological data can be akin to aviation “black box” technology,allowing the user to replay clinical actions leading up to medicalincidents.

At block 812, the request is received from a user to review journaledand physiological data corresponding to a period of time. The user maybe a clinician, hospital administrator, or the like, who wishes todetermine the cause of a problem in the healthcare of a patient. Forinstance, the user may wish to determine why clinicians failed torespond when a patient's SpO₂ dropped below safe levels.

At block 814, journaled data is retrieved for the specified period oftime from a journal database. This block may be performed by the journalmanagement module 725. At block 816, physiological data for thespecified period of time is retrieved from an RRDB. This block may beperformed by the RRDB management module 723. The journal data iscorrelated with the physiological data with respect to time at block818. This correlation may include reconstructing a timeline of medicalevents, with values of physiological parameters (optionally includingwaveforms) provided in the correct time sequence on the timeline. Insome embodiments, to facilitate this coordination between the RRDBmanagement module 723 and the journal management module 725, timestampsin each database 722, 724 may be synchronized when the data is stored.

The correlated data is output for presentation to the user at block 820.The output may include, for example, a graphical view of medical eventssuperimposed on physiological information (e.g., a waveform), or thelike. Many display formats may be used for the correlated data.

FIG. 9 illustrates an example graphical user interface (GUI) 900 formonitoring patients. The GUI 900 can be provided on a nurses' stationsystem or the like. The GUI 900 can also be displayed on a cliniciandevice.

The GUI 900 includes several display areas. In the depicted embodiment,the GUI 900 includes a patient status display area 910. The patientstatus display area 910 shows the status of multiple patients in ahospital or other clinical location. In an embodiment, patient statusdisplay area 910 depicts patient status for patients in a hospitaldepartment. Advantageously, in certain embodiments, the patient statusdisplay area 910 provides an “at-a-glance” view of multiple patients'health status.

The patient status display area 910 includes a plurality of patientstatus modules 912. Each patient status module 912 can correspond to apatient monitor that can be coupled to a medical patient. Each patientstatus module 912 can display a graphical status indicator 914. Anexample graphical status indicator 914 is shown in the screens 900 as aminiature patient monitor icon. The graphical status indicator 914 canselectively indicate one of several states of a patient monitor. In oneembodiment, four possible patient monitor states can be depicted by thegraphical status indicator 914. These include an alarm condition, a noalarm condition, patient context information status, and connectionstatus.

In various implementations, the graphical status indicator 914 changescolor, shape, or the like to indicate one of the different patientmonitor states. For example, if an alarm condition is present, thegraphical status indicator 914 could turn red to signify the alarm. Ifthere is no context information available for the patient (see FIG. 1),then the graphical status indicator 914 could turn yellow. If the deviceis not connected to the patient or the network, then the graphicalstatus indicator 914 could turn gray. And if there is no alarmcondition, if there is context information, and if the patient monitoris connected to the patient and the network, then the graphical statusindicator 914 could turn green. Many other colors, symbols, and/orshapes could be used in place of or in combination with theabove-described embodiments.

Advantageously, the graphical status indicator 914 shows at a glance thestatus of a patient monitor. Thus, in the patient status display area910, several graphical status indicators 914 corresponding to severalpatients show an at-a-glance view for the patient monitors correspondingto these patients. A clinician can therefore readily see the needs thata patient might have with regards to alarms, connection status, andcontext information.

Currently available graphical user interfaces for nurses' stationcomputers tend to show a plurality of wave forms or changingphysiological parameter numbers for each patient. This method ofdisplaying patient information can be cluttered, confusing, and evenhypnotic in some situations. Nurses working on a night shift, forinstance, may find it difficult to concentrate on an alarm when severalother patients' indicators on the display have changing numbers,changing waveforms, or the like. In contrast, in the graphical interfaceherein described, when the graphical status indicator 914 indicates analarm condition, this alarm condition can stand out and be immediatelyrecognized by the clinician.

Moreover, the graphical status indicator 914 simplifies the first levelof analysis that nurses tend to perform. In currently available devices,nurses often have to analyze waveforms at the nurses' station todetermine the health status of a patient. However, using the screens900, a nurse need not interpret any waveforms or changing parameters ofthe patient, but instead can rely on the graphical status indicator 914that indicates the presence of an alarm.

In certain embodiments, the patient status modules 912 can be selectedby a single mouse click or the like. Selecting a patient status module912 in one embodiment can bring up a patient monitor view area 920. Thepatient monitor view area 920 shows a view of a patient monitorcorresponding to a selected patient status module 912. In certainimplementations, the patient monitor view area 920 can show a view ofthe screen from the actual patient monitor device at the bedside of thepatient. Thus, a clinician can readily recognize the physiologicalparameters of the patient in a format that the clinician is likelyfamiliar with. The patient monitor view area 920 is currently receivingphysiological information from a patient.

A history view area 930 in certain implementations can show medicalevent data corresponding to a selected patient monitor status module912. This medical event data can be obtained from a journal database forinclusion in the GUI 900. The historical view 930 can show, for example,when a sensor was connected or disconnected from a patient, when alarmswere active, and when a patient was admitted to the hospital ordepartment. Although not shown, the history view area 930 can also beconfigured to show trend data obtained from an RRDB instead of, or inaddition to, the journaled data.

Other features are described in U.S. patent application Ser. No. ______(Attorney Docket MASIMO.609P1), entitled “SYSTEMS AND METHODS FORSTORING, ANALYZING AND RETRIEVING MEDICAL DATA,” filed Oct. 14, 2010,the entire contents of which are hereby incorporated by referenceherein.

Transmission of Patient Information to Remote Devices

In some embodiments, the patient monitoring devices described herein arecapable of transmitting patient information to one or more remotedevices for review by a clinician. For example, such remote devices caninclude remote computers, smart phones, PDAs, etc. This is usefulbecause it enhances the ability of a clinician to monitor a patient'scondition remotely. For example, the clinician need not be at thepatient's bedside or even at a hospital or other patient care facilityin order to effectively monitor the patient's condition.

In some embodiments, any of the information collected by a patientmonitoring device (e.g., the patient monitoring devices describedherein) can be transmitted to a remote device. Such information caninclude, for example, values, trend data, etc. for a medical parameter(e.g., blood oxygen saturation, pulse rate, respiration rate, etc.). Itcan also include video of the patient and/or audio from the patientand/or the patient's room. For example, video cameras and/or microphonescan be provided in the patient's room. In some embodiments, a videocamera and/or microphone is incorporated with, for example, a medicalmonitoring device, such as those described herein. The video camera canimage the patient using visible light when the ambient light in thepatient's room is of sufficient intensity. The video camera can also becapable of detecting, for example, infrared light when the patient'sroom is too dark to provide video of acceptable quality using visiblelight. The video camera can also include an infrared illumination sourceto illuminate the patient and/or his or her surroundings. In someembodiments, the video camera includes an ambient light sensor that canbe used to automatically switch the video camera into infrared mode whenthe ambient light falls below some threshold. The light sensor can alsobe used for switching on an infrared illumination source if one isincluded.

The transmission of patient information (e.g., medical parameter data,video/audio of the patient, etc.) can be made using, for example, one ormore communication networks (e.g., computer networks such as LANs,WLANs, the Internet, etc., telephone networks, etc.). In someembodiments, one or more communication networks that are entirely orpartially physically located in a hospital or other patient care centercan be used. In some embodiments, external communication networks can beused to reach remote devices throughout the world. Thus, clinicians canremotely obtain a vast amount of information regarding the condition oftheir patients regardless of the clinician's location. In someembodiments, the clinician may also have the capability to directlycommunicate with the patient. For example, a patient monitoring devicecould include a speaker for broadcasting audio from the clinician'sremote device to the patient. Similarly, a patient monitoring devicecould include a display for showing video from the clinician's remotedevice (e.g., video teleconferencing). In this way, the exchange ofinformation can be bidirectional to allow the clinician to directlyinteract with the patient.

Hospital Systems with Location Awareness of Devices and Clinicians

Advanced monitoring systems are capable of displaying many differentphysiological parameters in many different formats. One possibledrawback to this substantial performance capability and displayflexibility is that excessive information may be presented to thecaregivers that use these systems. These caregivers may includephysicians, respiratory therapists, registered nurses, and otherclinicians whose uses of the monitoring systems may vary from the takingof routine vital signs to the diagnosis and treatment of complexphysiological conditions to clinical research and data collection.

Patient monitoring devices, such as those described herein, may includea keyboard, touchscreen, or other input device to allow a clinician tointeract with the device. Such user interface devices can be used toallow a clinician to input login information, such as, for example ausername and password. In some cases, a monitoring device may require aclinician to login to the device, for example, before permitting accessto one or more of the functions offered by the device, and/or beforepermitting access to certain information available at the device. Thenurses' station, or central monitoring station, as described herein, isan example of one such monitoring device that may require a clinician tologin in order to use it. Bedside patient monitors may require aclinician to login before initializing monitoring of a new patient. Evenwhere a clinician is not required to login to a patient monitoringdevice before using it, the device may still require some type ofinteraction with an input device in order to cause it to take aparticular action from amongst a set of available actions offered by thepatient monitoring device.

For example, user input may be required in order to configure a patientmonitoring device in a desired manner. In some embodiments, a clinicianmay use an input device to change the content offered on the display ofthe patient monitor device, or the formatting of the content, to suithis or her preferences. In some instances, a nurse may use the inputdevice to manually configure the central monitoring station to displayonly monitoring information for those patients that are assigned to thatparticular nurse rather than displaying, for example, all the patientson the entire floor. A clinician may also use an input device to alterpatient monitoring settings such as, for example, options forcalculating physiological parameter values from raw data, alarm types,physiological parameter alarm limits (e.g., alarm thresholds), etc.

Given the time demands placed on clinicians in busy hospitals, thisprocess of manually interacting with a patient monitoring device by, forexample, physically manipulating an input device can be burdensome,especially when it may need to be repeated over and over throughout theday. In some cases, the time required to manually interact with apatient monitor device in order to access a particular function orconfigure the device can even jeopardize a patient's well-being inparticularly urgent circumstances. For at least the foregoing reasons,it would be advantageous for hospital equipment, such as bedside patientmonitors, central monitoring stations, and other devices, to have thecapability to automatically detect the presence of a clinician, and to,for example, take some predetermined action based on the identity of theclinician whose presence is detected.

In some embodiments, a proximity display monitor advantageously adaptsan advanced monitoring system to various user needs and preferences byadapting the display to the current observer according to, for example,preference, priority, or user acknowledgement. Accordingly, displayedparameters and formats may be chosen by default according to apredefined user class or customized for particular individuals or groupsof individuals. One method of identifying persons in the vicinity of aproximity display is by an ID tag or other token. The ID tag maycommunicate the user to the proximity display monitor viaradio-frequency identification (RFID) or wireless radio transmission asexamples. If multiple users are in range of a proximity display monitor,a priority scheme or a user acknowledgment may be used to determinewhich users are accommodated.

In some embodiments, a proximity display monitor has a monitor and aninterconnected sensor, the sensor transmits optical radiation into atissue site and generates a sensor signal responsive to the opticalradiation after attenuation by pulsatile blood flow within the tissuesite. The monitor may compute physiological parameters responsive to thesensor signal and utilize a proximity display to show the physiologicalparameters on screen according to a display preference associated with auser in proximity to the monitor. A display can be incorporated with themonitor so as to present the physiological parameters for viewing by acaregiver. A transceiver can be incorporated with the monitor and may beresponsive to an identification signal. The identification signal cancorrespond to a caregiver. A transmitter carried by the caregiver cansend the identification signal over a range, for example, approximatingthe distance from the monitor that a person can reasonably view thedisplay. A preferred screen can present the physiological parameters onthe display according to the display preference associated with thecaregiver as indicated by the identification signal.

In some embodiments, a proximity display monitor comprises a monitorhaving a display and a wireless transceiver. The wireless transceivercan be responsive to identification signals which indicate the proximityto the monitor of any users, who have corresponding display preferences.Preferred screens may present the physiological parameters on thedisplay according to the display preferences.

In some embodiments, a proximity display monitor has an optical sensorattached to a fleshy tissue site. A sensor signal may be responsive tooptical radiation transmitted by the sensor and detected by the sensorafter absorption by pulsatile blood flow within the tissue site. Thesensor signal can be communicated to a monitor, which processes thesensor signal so as to derive physiological parameters responsive toconstituents of the pulsatile blood flow. The identity of a user inproximity to the monitor can be wirelessly signaled to the monitor. Ascreen preference, for example, can be determined from the user identityand used to display the physiological parameters on a monitor display.

In some embodiments, a proximity display monitor comprises a processorand a display. The processor can be responsive to a sensor signalgenerated from optical radiation transmitted into a fleshy tissue siteand detected after attenuation by pulsatile blood flow within the tissuesite. The processor can be configured to calculate a plurality ofphysiological parameters indicative of constituents of the pulsatileblood flow. The display may provide a visual representation of thephysiological parameters values for viewing by proximate users. Awireless communications means can determine the identities of proximateusers. Screen preference means may present the physiological parameterson the display. A lookup table means can relate the user identities tothe screen preferences.

FIG. 10 illustrates a physiological measurement system having anoninvasive sensor 1010 attached to a tissue site 1000, a patientmonitor 1020, and an interface cable 1030 interconnecting the monitor1020 and the sensor 1010. The physiological monitoring system mayincorporate pulse oximetry in addition to advanced features, such as amultiple wavelength sensor and advanced processes for determiningphysiological parameters other than or in addition to those of pulseoximetry, such as carboxyhemoglobin, methemoglobin and total hemoglobin,as a few examples. The patient monitor 1020 has a proximity display 1021that presents measurements of selected physiological parameters and thatalso provides visual and audible alarm mechanisms that alert a caregiverwhen these parameters are outside of predetermined limits. The patientmonitor 1020 also has keys 1022 for controlling display and alarmsfunctions, among other items. The proximity display 1021 and keys 1022provide a user interface that organizes many parameters so that acaregiver can readily ascertain patient status using, for example, aportable, handheld device.

FIG. 11 illustrates various screens 1150 for a proximity display 1021(FIG. 10) advantageously configured to respond to the presence of aparticular user 1130 and to that user's display preference. Users may beany of various caregivers such as treating physicians or attendingnurses. In an embodiment, the proximity display 1021 (FIG. 10) may alsorespond to any of a particular group of users.

As described with respect to FIG. 13, below, the presence or proximityof a particular user or group of users to the monitor 1020 (FIG. 10) maybe determined by a user wearing an RFID (radio frequency identification)tag or other wireless communications. Then, a particular screen orscreens can be presented on the display according to a predetermineddisplay preference associated with the user. In this manner, a proximitydisplay 1021 (FIG. 10) is tailored to the preferences of monitor users.An “RFID tag” or simply “tag” can include any wireless communicationdevice that can remotely identify a proximate user to a monitor. Tagsinclude, but are not limited to, devices in the form of badges, tags,clip-ons, bracelets or pens that house an RFID chip or other wirelesscommunication components. Tags also encompass smart phones, PDAs, pocketPCs and other mobile computing devices having wireless communicationscapability.

As shown in FIG. 11, by example, an anesthesiologist 1131 proximate themonitor is identified and the display is changed to a screen 1110showing pulse rate trend. When a nurse 1132 is proximate the monitor,the display is changed to a screen 1120 showing pulse oximetryparameters, a plethysmograph and alarm limits. When a respiratorytherapist 1133 is proximate the monitor, the display is changed to ascreen 1140 showing pulse oximetry, abnormal hemoglobin and perfusionindices.

In some embodiments, a proximity display monitor responds to thedeparture of all proximate users by automatically dimming the display toa reduced brightness setting. This feature advantageously avoidsdisturbance of a patient who is sleeping or attempting to sleep. In someembodiments, a proximity display monitor responds in a similar manner byautomatically silencing pulse “beeps” and other non-critical sounds whenthere are no proximate users.

FIG. 12 illustrates a proximity display monitor 1200 that responds to anearby user 1280 so as to display calculated parameters according to auser display preference. As shown in FIG. 12, the proximity displaymonitor 1200, in some embodiments, has a front-end 1210 that interfaceswith an optical sensor (not shown). The optical sensor generates asensor signal responsive to pulsatile blood flow with a patient tissuesite. An optical sensor is described in U.S. patent application Ser. No.11/367,013 titled Multiple Wavelength Sensor Emitters, cited above. Thefront-end 1210 conditions and digitizes the sensor signal 1212, which isinput to a digital signal processor (DSP) 1220. The DSP 1220 derivesphysiological parameters 1222 according to the sensor signal 1212. Thecalculated parameter values are communicated to a display driver 1230,which presents the parameters on the display 1270 according to apredetermined format. A monitor having a front-end and DSP is describedin U.S. patent application Ser. No. 11/366,208 titled NoninvasiveMulti-Parameter Patient Monitor, cited above.

Also shown in FIG. 12, the proximity display monitor 1200 has atransceiver or receiver 1240, a lookup table 1250 and displaypreferences 1258. The proximity display monitor 1200 may also include acommunication module for communicatively coupling the proximity displaymonitor 1200 to other patient monitoring devices, such as, for example,other bedside patient monitors, a central patient monitoring station,etc. The user 1280 has an ID tag 1260 that identifies the user 1280 tothe transceiver 1240. When the user 1280 is in the vicinity of theproximity display monitor 1200, the ID tag 1260 is able to communicatewith the transceiver 1240 so as to identify the user 1280. In anembodiment, the transceiver 1240 is an RFID reader and the ID tag 1260has an embedded RFID chip containing a user code 1252. In anotherembodiment, the transceiver 1240 complies with one or more short-rangewireless communications standards, such as Bluetooth®. The user 1280 caninitiate communications with the proximity display monitor 1200 by, forexample, pressing a button or similar initiator on the ID tag 1260, anda user code 1252 is transmitted to the transceiver 1240. The transceiver1240 communicates the user code 1252 to the DSP 1220. The DSP can accessthe lookup table 1250 so as to derive a display preference 1258 from thereceived user code 1252. The lookup table 1250 may be stored locally inthe proximity display monitor's memory, or the lookup table may bestored remotely, for example, at a central patient monitoring station,which is communicatively coupled to the bedside proximity displaymonitor. The display preference 1258 indicates the display parameters1222 and screen format 1224, which are communicated to the displaydriver 1230.

Further shown in FIG. 12, in some embodiments, the lookup table 1250relates the user code 1252 to a caregiver ID 1256 and a priority 1254.When multiple users are in the vicinity of the proximity display monitor1200, the priority 1254 determines which display preference 1258 is usedto configure the display 1270.

FIG. 13 illustrates a display preference screen 1300, which providesinformation for a particular row of the look-up table 1250 (FIG. 12). Asetup or registration procedure allows users to specify one or moreprofiles including, for example, a display preference and variousoptions for calculating parameters and triggering alarms.

FIG. 14 is a schematic diagram of a patient monitoring device 1400 thatis capable of automatically detecting the presence of a clinician token1410. In some embodiments, the clinician token 1410 is a portable itemmeant to be, for example, worn or carried by a clinician throughout theday. The patient monitoring device 1400 is able to recognize thepresence of the clinician based upon the presence of that clinician'stoken.

The patient monitoring device 1400 includes a detector such as, forexample, a communication module 1402. The patient monitoring device 1400also includes a display 1404, and a processor 1406. The processor 1406can be used, for example, for carrying out clinically-useful tasks onthe basis of physiological information collected from one or morepatients (e.g., calculating physiological parameter values, determiningalarm conditions, outputting physiological information via a clinicianuser interface, notifying a clinician of an alarm condition, etc.) Thepatient monitoring device 1400 can also include other modules to assistin the monitoring of patients, as described herein (e.g., an interfacefor receiving physiological information from a medical sensor orcomputer network, a user interface for facilitating interaction with aclinician, etc.). In some embodiments, the communication module 1402 isa transmitter, a receiver, or a transceiver. Other types ofcommunication modules can also be used. In some embodiments, thecommunication module 1402 is a short-range transceiver. The short rangetransceiver can be, for example, a Bluetooth-enabled transceiver.Bluetooth is a wireless protocol for exchanging data between devicesover relatively short distances. The communication module 1402 can alsobe an infrared transceiver, an RFID tag, or any other means ofcommunication (e.g., short-range communication).

The communication module 1402 is capable, in some embodiments, ofdetecting signals from a remote device within a detection area 1420. Thesize of the detection area of 1420 can be determined by, for example,the power levels of communication signals from the communication module1402. The size of the detection area 1420 may also be affected by thesurroundings of the patient monitoring device 1400. In some embodiments,the detection area 1420 is configured to have a radius of 30 feet orless. In some embodiments, the radius of the detection area 1420 is 20feet or less. In some embodiments, the radius is 10 feet or less, whilein some embodiments, the radius is 5 feet or less, or 3 feet or less. Insome embodiments, the patient monitoring device 1400 has multipledetection areas. Such detection areas could be, for example, differentdistance ranges from the patient monitoring device 1400. The patientmonitoring device 1400 can be configured to perform different actions inresponse to detection of a clinician token in each of the differentdetection areas.

The clinician token 1410 can likewise include a communication module1412, which can be, for example, a transmitter, a receiver, or atransceiver, though other types of communication modules may also beused. As is the case with the patient monitoring device 1400, thecommunication module 1412 included with the clinician token 1410 may bea short range transceiver, such as, for example, a Bluetoothtransceiver. The patient monitoring device 1400 is capable of detectingthe presence of a clinician based on, for example, recognition of one ormore communication signals from a clinician token 1410. A communicationsignal from the clinician token 1410 may come, for example, in responseto a communication initiated by the patient monitoring device 1400, orthe communication signal from the clinician token 1410 may be initiatedby the clinician token itself. Many different methods can be used forinitiating, for example, wireless communication between remote devices.

The clinician token 1410 may also carry information, for example, in amemory. The memory may be, for example, volatile or nonvolatile memory.The information may be hardwired into the clinician token 1410 orprogrammable. In some embodiments, the clinician token 1410 includes aclinician ID 1414 that is unique to the clinician to whom the cliniciantoken 1410 is assigned. The clinician token 1410 may also include otherinformation such as, for example, a clinician's login information (e.g.,user name and password), a code or other indicator for initiating apredetermined action to be performed by the patient monitoring device1400 upon recognition of the clinician's presence (logging in theclinician, setting configuration preferences of the patient monitoringdevice 1400, enabling a function, etc.).

The clinician token 1410 may also include an input module 1416 thatallows the clinician to cause the communication module 1412 to remotelycommunicate with, for example, the patient monitoring device 1400, orsome other device that forms a part of the hospital's patient monitoringnetwork. For example, the input module 1416 may include one or morebuttons, or other input devices, that allow the clinician to initiate acommunication with the patient monitoring device 1400 for the purpose ofhaving that device recognize the clinician's presence. In addition, theclinician may use the input module 1416 to, for example, call in anemergency response team if the clinician discovers that a particularpatient is in need of emergency attention, or to silence a monitoringalarm. The input module 1416 can also be used for other purposes,depending upon the application.

In some embodiments, the clinician token 1410 is a cell phone, notebookcomputer, PDA device, headset, etc., any one of which may be, forexample, Bluetooth-enabled. In some embodiments, the clinician token1410 is the pager, or other notification device, used to notifyclinicians of physiological parameter alarm conditions, as describedherein. In some embodiments, the clinician token 1410 is an active orpassive RFID tag. An active RFID tag may be WiFi-enabled, for example.In some embodiments, the clinician token 1410 is a barcode (e.g.,two-dimensional or three-dimensional). In some embodiments, theclinician token 1410 is a part of the clinician's body. For example, theclinician token 1410 may be a fingerprint, a retina, the clinician'sface, etc. In such embodiments, the clinician ID 1414 is actually aunique biometric signature of the clinician. The communication module1402 may be selected based upon the type of clinician token 1410 withwhich it is to communicate. For example, the communication module 1402in the patient monitoring device 1400 may be an RFID interrogator, abarcode scanner, a fingerprint scanner, a retina scanner, a facialrecognition device, etc.

In some embodiments, the clinician token 1410 is advantageously aconsumer device that can be registered with the patient monitoringdevice 1400 but that has no prior connection or relationship with, forexample, the patient monitoring device 1400, a patient monitoringsystem, the hospital, etc. For example, the clinician token 1410 can bea consumer device that is not designed specifically for the purpose ofcommunicating with the patient monitoring device 1400, or any otherdevice configured to be able to detect the presence of the cliniciantoken. Many clinicians will already own, for example, a cell phone whichis carried on the clinician's person throughout the day for theclinician's personal use. In some embodiments, the clinician's personalelectronic device can function as the clinician token 1414, for example,after a registration process that will be described herein. This can beadvantageous because it does not require investment on the part of thehospital or other caregiver facility to provide each clinician with aspecial-purpose clinician token 1410. Nevertheless, in some embodiments,the clinician token 1410 is a special-purpose device provided to theclinician for the primary purpose of operating with, for example,patient monitoring devices (e.g., 1400) having presence detectionfunctionality.

In some embodiments, the clinician token 1410 is capable of respondingto, for example, interrogation from a patient monitoring device onlywith a fixed response signal (e.g., a clinician ID 1414). In someembodiments, however, the clinician token 1410 is capable oftransmitting multiple, and/or variable, signals and information to thepatient monitoring device 1400. The clinician token 1410 may include aprocessor capable of executing, for example, software applications thatallow the clinician token 1410 the capability of a variety ofintelligent communications with the patient monitoring device 1400.

In some embodiments, a registration process is completed before theclinician token 1410 is used with the patient monitoring device 1400 toimplement presence detection functionality. For example, during aregistration process, the clinician token 1410 may be endowed with aunique clinician ID 1414 assigned to a particular clinician. Thisclinician ID may be stored in a database that is, for example,accessible by the patient monitoring device 1400 such that the patientmonitoring device 1400 can determine the identity of the clinician basedupon the clinician ID 1414 stored in the clinician token 1410. Theclinician ID 1414 can also be associated in the database with, forexample, the clinician's assigned login information for accessing thepatient monitoring device 1400.

The database can also store an indication of the action, or actions,that the clinician desires a particular patient monitoring device totake upon detection of the clinician's presence. The database can storethe clinician's configuration preferences for the patient monitoringdevice. For example, the particular physiological parameters and othermonitoring information that are shown on the display 1404 of the patientmonitoring device 1400 may be configurable. In the case of bedsidepatient monitors, for example, the display 1404 may be capable ofshowing numerical indicators of a particular physiological parameter,graphical indicators of the physiological parameter, visual alarms,multiple physiological parameters simultaneously, signal quality ofphysiological parameter signals from a patient sensor, etc. Theclinician's configuration preferences can indicate to the monitoringdevice 1400 what type of information to display and how to format thedisplayed information. The clinician's configuration preferences for thepatient monitoring device 1400 can also include patient monitoringsettings such as, for example, physiological parameter alarm limits.

In the case of, for example, a central monitoring station, such as thetype described herein, the clinician's configuration preferences maylikewise include the type and display format of a physiologicalparameter, or other monitoring information, that is shown for each ofthe patients being monitored at the central monitoring station. Inaddition, the clinician's configuration preferences can include a fixedor dynamic list of patient rooms, or patient names, to be displayed atthe central monitoring station. These rooms, or patients, can be thosecurrently assigned to that particular clinician, for example. Ingeneral, however, the clinician's configuration preferences that areassociated with the clinician ID 1414 can include any configurablefeature, aspect, or function of the patient monitoring device 1400.

In some embodiments, the database can be configured to receive a varietyof input information to define, for example, different action to beperformed by a monitoring device 1400 upon detection of the clinician'stoken. Inputs to the database can include the clinician ID, the strengthof the signal from the clinician's token, the estimated distance of thedetected clinician token from the monitoring device, the length of timeof detected presence of the token, a clinician priority level, the timeof day, the room or hospital ward associated with the monitoring devicethat has detected the clinician's presence, etc. Based upon this input,the database can output a set of actions to be performed by the patientmonitoring device upon detection of the clinician. Alternatively, or inaddition, such actions and preferences can be determined using logicalrules applied to the input information.

The database can be stored locally by the patient monitoring device1400. Alternatively, or in addition, the database can be stored remotelyby a device that is communicatively coupled to the patient monitoringdevice 1400. For example, in some embodiments, a bedside patient monitoris communicatively coupled to a central monitoring station, as describedherein. In some embodiments, this communication link is via a wirelessnetwork. In such embodiments, when the bedside patient monitor detectsthe presence of a clinician, it can receive a clinician ID and/or otherinformation from a clinician token. The bedside patient monitor can thencommunicate this information to the remote database maintained by thecentral monitoring station. The bedside patient monitor can alsotransmit to the central monitoring station other input information, asidentified above (e.g., the estimated distance of the clinician tokenfrom the bedside patient monitor, the length of time the clinician tokenhas been present in the detection area, and/or other informationcollected from, or using, the clinician token).

The central monitoring station can then query the database using thisinformation to determine any actions associated with the detection ofthe clinician's token under the circumstances indicated by the inputinformation. Once an associated action has been determined from thedatabase, the central monitoring station can then command of the bedsidepatient monitor as to the action it should take in response to detectionof the clinician's presence.

In some embodiments, the database is remotely accessible such thatactions or preferences can be conveniently stored, updated, and accessedby users. For example, the database can be remotely accessible via a webserver. In some embodiments, the database is stored locally by a patientmonitoring device (e.g., a bedside patient monitor) instead of remotely.In such embodiments, however, the locally-stored database maynevertheless be periodically remotely updated by, for example, thecentral monitoring station.

The database can associate with the clinician ID 1414 a particularaction that the clinician may wish to initiate upon entering thedetection area 1420 of the patient monitoring device 1400. Examples ofsuch actions that can be initiated automatically upon detection of theclinician's presence are described herein. In addition, in someembodiments, the database can also associate with the clinician ID 1414a priority level. The priority level can indicate which clinician shouldbe given priority access to a medical monitoring device 1400, forexample, when multiple clinicians are detected in the detection area1420 simultaneously.

In some embodiments, the clinician's assigned login information,monitoring device configuration preferences, list of actions toautomatically initiate upon recognition of the clinician's presence,priority level, and/or other information can be stored by the cliniciantoken 1410 itself. In such embodiments, this information may betransmitted directly to the patient monitoring device 1400 by theclinician token 1410 as opposed to the patient monitoring device 1400obtaining the information from a database using the clinician ID 1414stored on the token 1410. Other methods can also be used in order toassociate, for example, a clinician ID 1414 with a predetermined action(e.g., logging in, configuration change, etc.) that the clinician wishesthe patient monitoring device 1400 to take or assume when the clinicianis in the detection area 1420 of the device 1400.

In some embodiments, once a registration process is complete, thepatient monitoring device 1400 is capable of detecting the presence of aparticular clinician based upon the clinician's token 1410, and oftaking, for example, a clinician-specific action based upon recognitionof the clinician's presence. In some embodiments, the processor 1406 ofthe patient monitoring device 1400 is configured to execute detectionlogic 1408 for determining when a clinician token 1410 is or is notpresent in the detection area 1420 of the monitoring device 1400. Insome embodiments, the detection logic 1408 is a set of rules or othercriteria that must be satisfied before a clinician token 1410 isdetermined to be present in the detection region 1420, or before someclinician-specific action is performed.

FIG. 15 is a flowchart illustrating detection method 1500 for detectingthe presence of a clinician token (e.g., 1410) within the detectionregion of a patient monitoring device. The detection method 1500 canbegin, for example, at a waiting state 1502 where the patient monitoringdevice 1400 has not detected the presence of a clinician. In the waitingstate 1502, the patient monitoring device 1400 can allow manual access,for example, to the features and information that can be provided by thedevice 1400. In the waiting state 1502, the patient monitoring devicecan also allow manual configuration of the device, or interaction withthe device, by a clinician using an input device such as a keyboard,mouse, or touchscreen. Thus, the waiting state 1502 advantageouslyallows clinicians who may not have an assigned clinician token 1410 tonevertheless use and interact with the patient monitoring device 1400.

At decision block 1504, the processor 1406 executes the detection logic1408 to determine whether a signal is detected from a clinician token1410. For example, in some embodiments, the communication module 1402 ofthe patient monitoring device 1400 may, for example, continuously, orperiodically, transmit a clinician token discovery signal. At decisionblock 1504, the processor 1406 can determine whether a response has beenreceived from a clinician token 1410 to the patient monitoring device'sdiscovery signal. Alternatively, or additionally, the clinician token1410 can be configured to, for example, continuously, or periodically,transmit a discovery signal which the patient monitoring device 1400 candetect. Response signals from the clinician token 1410 can include, forexample, the clinician ID 1414 or other information. If no signal isdetected from a clinician token 1410, then the detection method 1500returns to the waiting state 1502. If, however, a signal from aclinician token 1410 is detected, then the detection method 1500 canproceed to the next decision block 1506.

At decision block 1506, the processor 1406 executes the detection logic1408 to determine whether the detected signal from the clinician token1410 exceeds a signal strength threshold value. This test can be useful,for example, as an estimate of the physical distance between theclinician token 1410 and the patient monitoring device 1400. Forexample, the patient monitoring device 1400 may be configured such thatwhether or not a detection event occurs, and/or the particularpredetermined action it takes upon detection of a clinician, isdependent upon the estimate of the physical distance between theclinician and the patient monitoring device 1400. This may be useful,for example, in the case of a central monitoring station that is near ahigh traffic area where many clinicians regularly pass by. In suchsituations it may be advantageous to set the signal strength thresholdused in decision block 1506 at a relatively high level so as to limitthe clinician detection events to situations where a clinician is arelatively small distance away from the central monitoring station.Thus, the signal strength threshold can be configurable based, forexample, upon a desired physical distance from a clinician token 1410before recognizing a clinician presence detection event. If the signalstrength of the signal detected from a clinician token 1410 is below thesignal strength threshold used by the decision block 1506, then thedetection method 1500 returns to the waiting state 1502. If, however,the signal strength exceeds the threshold, then the detection method1500 can proceed to the next decision block 1508.

As discussed above, signal strength from a clinician token 1410 can beused to determine when to recognize a detection event. For example, thesignal strength from the clinician token can be used to determine anestimate of the distance between the clinician token 1410 and thepatient monitoring device 1400. However, some variation may exist in thesignal strength detected from two different clinician tokens 1410 evenif the two clinician tokens are located at substantially the samedistance from the patient monitoring device. Such signal strengthvariations can result from, for example, the two clinician tokens beingdifferent makes or models, from the two tokens being worn differently(e.g., one of the tokens being worn inside a clinician's clothing whilethe other is worn outside a clinician's clothing), etc. In someembodiments, a signal strength correction value may be associated witheach clinician token. This can be done, for example, by associating asignal strength correction value with the clinician ID from the token inthe database which stores actions and preferences associated with theclinician token.

The signal strength correction value can be used to adjust, for example,the estimated distance between a given clinician token and the patientmonitoring device. For example, a clinician token that is known totransmit a relatively strong signal at a given distance (e.g., comparedto other clinician tokens at the given distance) can be associated witha signal strength correction value that increases the distance estimatefor that clinician token. Similarly, a clinician token that is known totransmit a relatively weak signal at a given distance (e.g., compared toother clinician tokens at the given distance) can be associated with asignal strength correction value that decreases the distance estimatefor that clinician token. In some embodiments, the signal strengthcorrection value for a clinician token can be determined based uponfactors that may include, but are not limited to, the make and model ofthe clinician token, the user's preference in wearing the token, theoperating environment of the token, etc.

At decision block 1508, the processor 1406 executes the detection logic1408 to determine whether the signal strength of the signal from theclinician token 1410 has exceeded the signal strength threshold for aproximity time that is greater than a time threshold. This test can beuseful to avoid recognizing a clinician presence detection event incases where a clinician passes nearby the patient monitoring device 1400but does so only transiently, not remaining within the detection region1420 for a long enough period of time to merit a clinician presencedetection event. This test can likewise help eliminate false clinicianpresence detection events in high-traffic areas around a patientmonitoring device 1400 where many different clinicians routinely andregularly pass by. The proximity time threshold used by the decisionblock 1508 can be configurable. In some embodiments, the proximity timethreshold may be set at, for example, 1 second, 2 seconds, or 5 seconds.Other proximity times can also be used, however. If the proximity timefor a detected clinician token 1410 does not exceed the proximity timethreshold used by decision block 1508, then the detection method 1500returns to, for example, the waiting state 1502. If, however, theproximity time of the clinician token 1410 exceeds the proximity timethreshold, then the detection method 1500 can proceed to block 1510.

At block 1510, a clinician presence detection event is recognized. Atsuch time, the patient monitoring device 1400 can enable or initiate,for example, some predetermined action based upon the clinician identityassociated with the recognized clinician token 1410. For example, thepatient monitoring device 1400 can login the clinician, change aconfiguration setting, authorize some action or feature that istypically restricted absent the presence of a clinician, etc. In thedetection method 1500 illustrated in FIG. 15, whether or not a clinicianpresence detection event occurs is dependent upon the signal strength ofa signal from the clinician token 1410 as well as the length of timethat the signal from the clinician token 1410 exceeds a signal strengththreshold. In some embodiments, however, a clinician presence detectionevent can be recognized based only on signal strength from the cliniciantoken 1410, or based only on the length of time that a signal isdetected from a clinician token 1410.

In some embodiments, other factors can be included in the detectionlogic 1408, whether alone or in combination with signal strength fromthe clinician token 1410 and proximity time. For example, therecognition of a clinician presence detection event can be based, atleast in part, on the identity of the clinician (some patient monitoringdevices 1400 may only be accessible to certain clinicians). In addition,the recognition of a clinician presence detection event can be basedupon the assigned priority of the clinician. For example, a nursesupervisor could be assigned a higher priority than other nurses on theshift such that the presence of the nurse supervisor will be recognizedby a patient monitoring device 1400 even when the presence of anothernurse has already been recognized by the device. The converse situation,however, may not result in a new clinician presence detection event; thedetection of a lower priority clinician may not result in a detectionevent if the presence of a higher priority clinician has already beenrecognized by the patient monitoring device 1400. The priority level isone example of a tiebreaker criteria that can be used by the detectionlogic 1408 in the event that multiple clinician tokens meet the otherrequirements to initiate a clinician detection event at the same time.Other criteria can also be used in this tiebreaker role.

It should be appreciated that a wide variety of factors can be includedin the detection logic 1408 depending upon the hospital, the type ofmedical equipment involved (e.g., patient monitoring equipment or someother type of medical device). In addition, such factors can beaccounted for in the detection logic 1408 in a variety of ways. Forexample, the detection logic 1408 can determine when thresholds areexceeded, when a Boolean expression is true or false, when a fuzzy logicexpression is true or false, when a mathematical equation is satisfiedor not, when a compound rule is satisfied or not, etc.

In some embodiments, a detection event can be recognized when theclinician token 1410 enters each of a plurality of detection areas. Thedetection areas can be overlapping or non-overlapping. For example, insome embodiments, the patient monitoring device 1400 may be configuredto recognize the presence of clinician tokens 1410 within each ofseveral distance ranges. Different actions and preferences can beassociated with a detection event for each distance range.

As an example, the patient monitoring device 1400 can be configured todetect the presence of a clinician within a first distance range of 0-5feet, within a second distance range of 5-15 feet, and within a thirddistance range of 15-30 feet. It should be appreciated, however, thatdifferent distance ranges can be used, whether overlapping or not, andany number of distance ranges can be used. As discussed herein, when thepatient monitoring device 1400 detects the clinician token 1410 withinone of these detection areas, a detection event is recognized. Thepatient monitoring device 1400 can be configured to perform a particularset of actions upon the occurrence of such a detection event. Asdiscussed herein, the set of actions can be registered to the cliniciantoken in a database that is communicatively coupled to the patientmonitoring device 1400. The set of actions that corresponds to eachdetection area may each be unique, or may share one or more commonactions.

In the foregoing example, the patient monitoring device 1400 can beconfigured to display a clinician's preferred set of measurements intext or graphical indicators with a large size when the clinician isdetected to have entered the third distance range so as to enablesatisfactory viewing of the display from a distance. When the clinicianenters the second distance range, the size of the text or graphicalindicators can be reduced to a medium size. Similarly, once theclinician enters the first distance range, the text or graphicalindicators can be reduced to a still smaller size. As another example,the audible volume of an alarm can be adjusted as the clinician movesfrom one distance range to another. For example, the audible volume ofan alarm can be louder when the clinician is in the third distancerange, while it can be made softer or turned off when the clinician isin the first distance range. It should be appreciated, however, that anyaction or preference of that patient monitoring device 1400 can beconfigurably associated with any detection area. It should also beappreciated that the distance ranges can be made arbitrarily small so asto provide, for example, relatively continuous changes in the size ofdisplay features, the volume of an alarm, etc.

Similarly, different detection events can be generated depending uponthe length of time that a clinician token has been recognized within agiven detection area. For example, multiple detection events can begenerated while a clinician token is within a particular detection areain accordance with multiple time ranges. As an example, a firstdetection event may be generated when the clinician token is presentwithin a given detection area for 0-3 seconds. A second detection eventmay be generated when the clinician token is present within thedetection area for 3-10 seconds. It should be understood, however, thatdifferent time ranges can be used, and any number of time ranges can beused. In addition, a set of patient monitoring device actions andpreferences can be associated with detection events resulting from eachtime range.

When a clinician detection event has been realized according to, forexample, the detection method 1500, the patient monitoring device 1400can respond in a number of different ways. For example, the patientmonitoring device 1400 can initiate a predetermined action based uponthe identity of the clinician whose token has been detected in proximityto the monitoring device. In some embodiments, the predetermined actionis that the patient monitoring device 1400 automatically logs theclinician in without requiring the clinician to, for example, physicallyinteract with an input device. This process saves the clinician timeand, in some cases, can also save patient lives. As described herein,the clinician's login information can be transmitted to the patientmonitoring device 1400 from the clinician token 1410, or it can beretrieved from a database using the clinician ID 1414 from the token1410.

In some embodiments, the patient monitoring device enables or disables aparticular feature based upon detection of the clinician token 1410. Forexample, the patient monitoring device may enable/disable menus andbuttons (e.g., alarm limit menu, alarm silence, all mute, etc.) basedupon the credentials of the detected clinician. In some embodiments, thepatient monitoring device 1400 begins transmission of patient monitoringinformation to a remote device upon detecting the presence of aclinician. For example, a bedside patient monitor capable of capturingbreathing sounds from a patient could automatically begin transmissionof those breathing sounds to the clinician's Bluetooth headset, which,incidentally, can serve as the clinician token 1410 as well. In otherembodiments, the patient monitoring device 1400 could begin transmissionof any type of monitoring information to a remote device via, forexample, the Internet upon detecting the presence of a particularclinician. For example, the patient monitoring device 1400 can transmitthe patient's oxygen saturation trend data to the clinician's computerfor later analysis and diagnosis. The patient monitoring device 1400 canalso transmit any other type of patient information (e.g., medicalparameter values and/or trend data, video and/or audio from thepatient's room, etc.) to, for example, the clinician's computer, or someother device, in response to detection of the presence of someparticular clinician in proximity to the patient monitoring device 1400.

In some embodiments, the patient monitoring device automatically updatesits configuration based upon configuration preferences of a detectedclinician. For example, the patient monitoring device 1400 could alterthe content of the information it displays or the format of theinformation that it displays. These configuration changes can be madebased upon settings that the clinician indicates during the registrationprocess for the clinician token 1410. An example of such an embodimentis illustrated in FIG. 16. In some embodiments, a patient monitoringdevice changes the layout of a display screen (e.g., the number andtypes of parameters shown, the waveforms shown, trends, and other screencontrols). Display layouts can be selected from predefined layouts, or aclinician can make a custom layout. The same is true of otherconfiguration settings. Configuration settings can be associated withclinicians at an individual user or group level. A hierarchy of layoutsmodes can be established for layout conflicts.

The patient monitoring device 1400 can also update other configurationsettings based upon registered preferences of the clinician. These caninclude physiological parameter alarm limits, alarm silence, all mute,averaging time, algorithm mode, etc., for example. In addition, thepatient monitoring device 1400 could automatically create some type ofreport, such as a report of all alarm conditions that have beenregistered by that monitor over a predetermined period of time.

In addition, alarm annunciation and behavior can be altered in responseto a clinician proximity detection event. For example, if the clinicianis approaching a bedside patient monitoring device 1400 that iscurrently registering an alarm condition, the alarm can automatically besilenced in recognition that the clinician has entered within a certainradius of the monitoring device 1400. In some embodiments, the way thatthe patient monitoring device 1400 notifies of an alarm condition can bedependent upon the physical location of a clinician. For example, if thepatient monitoring device 1400 detects an alarm condition while theclinician is already in proximity to the monitoring device, then it mayemit no audible alarm or a lower-volume audible alarm. Alarm volume canalso be adjusted in other ways based upon detected clinician presence.Similarly, in such a scenario, the patient monitoring device 1400 may beconfigured not to transmit an alarm to the central monitoring station.In some embodiments, a medical monitoring device does not notify or pageother clinicians in case of an alarm if a clinician is already present.Alarm notification behavior of the medical monitoring device can bealtered in a variety of ways based upon detected presence of aclinician. A medical monitoring device with clinician proximityawareness can allow a detected clinician to acknowledge his or herpresence. As long as clinician presence is detected, the length ofexpiry of alarms can be changed (e.g., made longer).

In some embodiments, the patient monitoring device 1400 iscommunicatively coupled to a patient's electronic medical record (EMR),as described herein. The detection of clinician presence can be used todetermine what data is transmitted to the EMR, and/or when that data istransmitted to the EMR. For example, the patient monitoring device 1400may measure and store data regarding a physiological parameter. When aclinician is detected in proximity to the patient monitoring device, theclinician can be automatically prompted whether to transmit certainphysiological parameter measurements, or other data, to the patient'sEMR. The clinician can review, for example, current or pastmeasurements, and determine whether such measurements should be recordedin the EMR.

While in some embodiments, a clinician is prompted whether to logphysiological parameter measurement values in the EMR, or elsewhere,when the clinician's presence is detected, in other embodiments suchdata could automatically be logged based upon detection of theclinician's presence. In either case, the patient monitoring device 1400may be capable of determining the quality of the physiological signalsupon which a particular measurement value is based using signalprocessing algorithms or other methods. If the patient monitoring device1400 determines that signal quality, and the corresponding degree ofconfidence in the measurement values derived therefrom, is low, then thepatient monitoring device may reduce the frequency with whichmeasurement values are transmitted to the EMR. The patient monitoringdevice may also reduce the amount of data that is transmitted to the EMRat a time. This variation in the frequency and/or the amount ofphysiological parameter data that is stored to the EMR based on thequality of the physiological parameter signals being measured can bepracticed with or without detecting the presence of a clinician nearby.

In some embodiments, the patient monitoring device 1400 responds todetection of a clinician's presence by changing the language in whichtextual information is displayed by the monitoring device in accordancewith language preferences of the clinician. In some embodiments, thepatient monitoring device identifies and executes on-deviceconfirmations that may be required for risk management based upon thedetected clinician(s) in proximity to the monitoring device. In someembodiments, the patient monitoring device logs the number of clinicianvisits to a patient's bedside, the time of presence of each visit, thelength of each clinician visit, the response time of clinicians toalarms, etc. A clinician may be permitted to chart parameters measuredby the monitoring device to, for example, an electronic medical recordwith credentials based upon detection of clinician identity. Many othertypes of actions and/or configuration changes, or combinations of thosedescribed herein, can also be caused to automatically be initiated basedupon the fact that a clinician has been detected in proximity to thepatient monitoring device 1400.

FIG. 16 illustrates an example graphical user interface 1600 of nurses'station or central patient monitoring station. The graphical userinterface 1600 includes features similar to those described with respectto FIG. 9. For example, the graphical user interface 1600 includes apatient status display area 1610. The patient status display area 1610includes a plurality of patient status modules 1612, each having agraphical status indicator 1614. The graphical user interface 1600 alsoincludes a patient monitor view area 1620 and a history view area 1630.

As illustrated in FIG. 9, the central patient monitoring stationincludes several patient status display areas, each showing monitoringinformation from a different patient. Unlike FIG. 9, however, whichshows the status of a number of patients larger than a single nursecould possibly attend to individually, FIG. 16 shows only those patientsassigned to a particular clinician. The display of the central patientmonitoring station can be automatically updated from that of FIG. 9, forexample, to that of FIG. 16 in recognition of the presence of aclinician. In this way, the clinician can quickly and conveniently checkthe status of each of his or her assigned patients at a glance by simplyapproaching the central patient monitoring station without having toactually physically interact with a central patient monitoring station.In addition, the proximity detection features described herein can beused to facilitate assignments of clinicians to patients at the nurses'station. For example, patients can be added to the view of FIG. 16automatically if the clinician has been detected in proximity to thepatient's bedside monitor within some predetermined period of time.

FIG. 17 is a flowchart illustrating a method 1700 for determining whento disable a clinician-specific action that had been previously enabledby a patient monitoring device 1400 based upon the detected presence ofthe clinician. The method 1700 begins at block 1702 where someclinician-specific action has been previously enabled, as describedherein. The method 1700 then proceeds to decision block 1704 anddecision block 1708. For example, the method 1700 may involve detectingwhether a previously-detected clinician remains in proximity to apatient monitoring device while simultaneously detecting whether ahigher priority clinician arrives in proximity to the patient monitoringdevice. For example, the process illustrated by decision block 1708 cangenerate an interrupt signal if the presence of a higher priorityclinician is detected.

At decision block 1704, the processor 1406 executes the detection logic1408 to determine whether the strength of a signal from the cliniciantoken 1410 has fallen below a signal threshold. This threshold can bethe same threshold as used by the decision block 1506 in FIG. 15.Alternatively, these two thresholds can be different to provide a degreeof hysteresis in the detection system to guard against the situationwhere a clinician token 1410 could be recognized as switching betweenthe present and absent states repeatedly in quick succession if thestrength of the signal from the clinician token 1410 happens to beapproximately equal to the selected threshold value. If the strength ofthe signal from the clinician token 1410 has not fallen below the signalthreshold, then the method 1700 returns to block 1702 where theclinician-specific action remains enabled. If, however, the strength ofthe signal from the clinician token 1410 falls below the threshold usedin decision block 1704, then the method 1700 proceeds to decision block1706.

At decision block 1706, the processor 1406 executes the detection logic1408 to determine whether the strength of the signal from the cliniciantoken 1410 has fallen below the signal threshold for an absence timethat is greater than a time threshold. Thus, the combination of decisionblocks 1704 and 1706 determine whether the clinician token has beenoutside of a particular range for a particular amount of time. In someembodiments, this time threshold can be variable depending upon, forexample, the content of information displayed by the medical monitoringdevice 1400. For example, if the monitoring device 1400 is displayingsensitive personal information, then the time threshold can berelatively short in order to protect the patient's confidentiality.

If the absence time does not exceed the time threshold used by thedecision block 1706, then the method 1700 returns to block 1702 wherethe clinician-specific action remains enabled. If, however, the absencetime exceeds the time threshold, then the method 1700 proceeds to block1710. At block 1710, the clinician is recognized as no longer being inproximity to the patient monitoring device 1400. Therefore, thepreviously-enabled clinician-specific action is disabled. At such time,the patient monitoring device 1400 can return to a state similar to thewaiting state 1502 described with respect to FIG. 15. In someembodiments, the action performed by the patient monitoring device 1400at block 1710 can substantially reverse any action taken by themonitoring device at block 1510 in FIG. 15. For example, if theclinician was automatically logged in to the patient monitoring device1400 when his or her presence was initially detected, then at block1710, that clinician can be logged out. Similarly, if the configurationof the monitoring device 1400 was changed based upon the detectedclinician's preferences, then, at block 1710, those configurationchanges can be restored to, for example, a default state.

With reference now to the decision block 1708, the processor 1406executes the detection logic 1408 to determine whether the presence of ahigher priority clinician has been detected. The detection of such aclinician can proceed, for example according to the detection method1500 described with respect to FIG. 15. As described herein, eachclinician can be assigned a priority value that can act as a tiebreakercriteria to determine the presence of which clinician to recognize whenmore than one clinician is detected. If no higher priority clinician isdetected at decision block 1708, then the method 1700 returns to block1702. If, however, a higher priority clinician is detected at decisionblock 1708, then the method 1700 may proceed to block 1710 where therecognition of the presence of the previously-detected clinician isrevoked, and the presence of the newly detected higher-priorityclinician is recognized.

FIG. 18 is a schematic diagram of a system for enabling a patientmonitoring device 1800 to automatically detect the presence of aclinician token 1810. The patient monitoring device 1800 and theclinician token 1810 can be similar, for example, to the patientmonitoring device 1400 and clinician token 1410 described herein withrespect to FIG. 14 except as otherwise indicated. In the embodimentillustrated in FIG. 18, the patient monitoring device 1800 detects thepresence of the clinician token 1810 with the assistance of, forexample, one or more WiFi access points 1830-1832. The WiFi accesspoints 1830-1832 can be advantageously distributed throughout thepatient care environment where patient monitoring is occurring. The WiFiaccess points 1830-1832 can operate based on IEEE 802.11 standards, forexample.

The communication module 1802 of the patient monitoring device 1800 canbe, for example, a WiFi-enabled radio for communicating with the WiFiaccess points 1830-1832. In some embodiments, the clinician token 1810is a WiFi-enabled RFID tag. By communicating with the WiFi access points1830-1832, the patient monitoring device 1800 can triangulate itsposition relative to that WiFi access points. Likewise, the position ofthe clinician token 1810 can be triangulated. Thus, the distributed WiFiaccess points 1830-1832 can be used by, for example, the patientmonitoring device 1800 in order to determine the approximate position ofthe clinician token 1810 with respect to the monitoring device 1800. Insome embodiments, the patient monitoring device 1800 may alsocommunicating directly with the clinician token 1810 in order to, forexample, enhance the position approximation determined using thedistributed WiFi access points 1830-1832.

FIG. 19 is a schematic illustration of a patient monitoring devicenetwork 1900 having a clinician proximity awareness feature. The patientmonitoring device network 1900 can be similar to those shown, forexample, in FIGS. 1, 2, 6, and 7. The patient monitoring device network1900 includes multiple bedside patient monitors 1902, 1912, 1922 formonitoring multiple patients 1906, 1916, 1926. In some embodiments, eachof the bedside patient monitors 1902, 1912, 1922 is similar to thoseshown in, for example, FIG. 14 (1400) and FIG. 18 (1800). The bedsidepatient monitors 1902, 1912, 1922 are capable of detecting the presenceof a clinician based upon the clinician tokens 1904, 1914, 1924. Theclinician tokens 1904, 1914, 1924 can be similar, for example, to thoseshown in FIG. 14 (1410) and FIG. 18 (1810).

The patient monitoring device network 1900 also includes a nurses'station 1932 for remotely monitoring each of the patients 1906, 1916,1926. The nurses' station, or central monitoring station, 1932 can besimilar to those described herein. The patient monitoring device network1900 may also include a registration database 1942. As described herein,the registration database 1942 can associate unique clinician IDs (e.g.,1414, 1814) carried by the clinician tokens 1904, 1914, 1924, 1934 withinformation for controlling the patient monitoring devices 1902, 1912,1922, 1932 when the tokens are in the presence of those devices. Forexample, the registration database 1942 can associate each uniqueclinician ID with login information, configuration preferences, andpredetermined actions for the monitoring devices to perform afterrecognizing the presence of a clinician.

In the illustrated patient monitoring device network 1900, each of thepatient monitoring devices 1902, 1912, 1922, 1932 can communicate withone another via the network 1950. In some embodiments, the network 1950uses open source communications standards in order to facilitatecommunication between various medical devices. Though not illustrated,the patient monitoring device network 1900 can also include WiFi accesspoints, page transmitters, pagers, and other devices described herein.

FIG. 20 is a schematic drawing of a hospital floor 2000 with distributedWiFi access points 2030-2034 that can be used to estimate the physicallocations of medical devices 2002, 2004, patients 2010, 2012, andclinicians 2014, 2016. The WiFi access points 2030-2034, or otherdetectors, can be distributed throughout the hospital floor, or otherphysical region, in order to provide WiFi coverage throughout thepatient care area. In some embodiments, the WiFi access points 2030-2034have respective coverage areas 2040-2044 that the overlap one another.In some embodiments, the WiFi access points 2030-2034 are populateddensely enough so that at least three coverage areas 2040-2044 of theWiFi access points 2030-2034 overlap in substantially every portion ofthe hospital floor in which it is desired to track the positions ofmedical devices 2002, 2004, patients 2010, 2012, and clinicians 2014,2016. The access points 2030-2034 can be mounted, for example, on or inwalls, on or in ceilings, etc.

The medical devices 2002, 2004 can be similar to others describedherein. For example, in some embodiments, the medical devices 2002, 2004are patient monitoring devices. In some embodiments, the medical devices2002, 2004 are fitted with tracking tags or tokens 2006, 2008. Thetracking tags 2006, 2008 can be similar to the clinician tokensdescribed herein. In some embodiments, the tracking tags 2006, 2008 areWiFi-enabled RFID tags, though other types of tracking tags may also besuitable. Each tracking tag 2006, 2008 can include an equipment ID.

As already discussed herein, the clinicians 2014, 2016 may carryclinician tokens 2022, 2024. The clinician tokens 2022, 2024 can besimilar to those described herein. For example, in some embodiments, theclinician tokens 2014, 2016 are WiFi-enabled RFID tags. In someembodiments, each patient 2010, 2012 may also be fitted with a patienttoken 2018, 2020. The patient tokens 2018, 2020 can be similar to theclinician tokens described herein. In some embodiments, the patienttokens 2018, 2020 are WiFi-enabled RFID tags. These may be worn asbracelets, or otherwise suitably affixed to the patients. Each patienttoken 2018, 2020 can include a patient ID.

The distributed network of WiFi access points 2030-2034 can be used tocommunicate with the medical device tracking tags 2006, 2008, theclinician tokens 2022, 2024, and the patient tokens 2018, 2020 for thepurpose of estimating the physical position of each of these tags andtokens in the hospital 2000. For example, the WiFi access points2030-2034 can be used to triangulate the position of each tag or token.

While FIG. 20 illustrates a distributed network of WiFi access points2030-2034 that can be used for detecting the positions of the trackingtags 2006, 2008, the clinician tokens 2022, 2024, and the patient tokens2018, 2020, other devices can also be used for similar purposes. Forexample, in some embodiments, the WiFi access points 2030-2034 areeliminated and medical devices 2002, 2004 with short range transceivers,or other detectors, are used in their place to create an ad hoc network.Each medical device 2002, 2004 can serve as a node in the ad hocnetwork, and each node can share information about, for example, thepatients 2010, 2012 and the clinicians 2014, 2016 around it. In someembodiments, the medical devices 2002, 2004 are Bluetooth-enabled,though other short range wireless communications standards can also beused.

If the hospital floor 2000 contains a number of medical devices that arearranged densely enough, then the distributed medical devices 2002, 2004can serve as a network for tracking the location of, for example,Bluetooth-enabled medical device tracking tags 2006, 2008, patienttokens 2018, 2020, and clinician tokens 2022, 2024. In such anembodiment, the physical location of each tracking tag or token may onlybe identifiable if it is located within the range of a Bluetooth-enabledmedical device. In addition, in some embodiments, the physical locationof each tracking tag or token may not be able to be preciselyidentified, as each Bluetooth-enabled medical device may only be able todetermine that the tracking tag or token is located somewhere within themedical device's detection area. Nevertheless, this level of trackingresolution may be sufficient in many cases.

In the embodiment illustrated in FIG. 20, a location monitoring servermay be communicatively coupled to the WiFi access points 2030, 2034. Thelocation monitoring server may be configured to track the estimatedposition of each medical device 2002, 2004, each patient 2010, 2012, andeach clinician 2014, 2016. The location monitoring server may include adisplay to show this location information. In addition, the locationmonitoring server, or some other device, may execute logic that can beuseful in enhancing features offered by the patient monitoring systemsdescribed herein. The location monitoring server may also becommunicatively coupled to the medical devices 2002, 2004.

The system illustrated in FIG. 20 can be used, for example, to enhancethe patient monitoring systems described herein. As already discussed,the patient monitoring systems described herein are capable of providingnotifications to clinicians when, for example, a monitored patient'sphysiological parameter (e.g., SpO2, respiratory rate, etc.) triggers analarm. In some embodiments, the clinician assigned to monitor thepatient is notified first by, for example, a page, e-mail, text message,etc. If the first-notifying clinician does not respond within a setperiod of time, the patient monitoring system may be configured toexecute an escalation algorithm whereby one or more additionalclinicians are notified of the patient's alarm condition. In someembodiments, the clinician notifications that are sent out when an alarmcondition exists can be controlled, at least in part, usinglocation-based rules. For example, location-based rules can be used todetermine which clinician is notified of an alarm condition initially,and which clinician, or clinicians, are notified if escalation becomesnecessary. The location-based rules can receive as inputs informationfrom the system illustrated in FIG. 20 regarding the physical locationsof, for example, patients 2010, 2012 and/or clinicians 2014, 2016.

The location-based rules can be dependent upon, for example, theabsolute or relative locations of the patient's 2010, 2012 and/or theclinicians 2014, 2016. For example, if the patient 2010 undergoes analarm condition, that patient's previously assigned clinician can firstbe notified so long as he or she is present on the same floor of thehospital (or some other domain). In some embodiments, the clinicianlocated the closest to the patient who is experiencing the alarmcondition can be notified regardless of whether the clinician waspreviously assigned to the patient. In some embodiments, the closestclinician to the patient experiencing the alarm condition can benotified only after the regularly-assigned clinician fails to respondwithin a certain amount of time. In some embodiments, a nearby clinicianis notified of the alarm condition if the alarm condition isparticularly urgent and requires immediate attention. Many otherlocation-based rules can also be implemented.

Location-based rules can also be used for controlling whether aclinician is permitted to deactivate an alarm. As disclosed herein, theclinician tokens 2022, 2024 may include an input module (e.g., 1416).One use for this input module is to remotely disable an alarm once theclinician has received notification of the alarm and is en route to thepatient. However, in some embodiments, a location-based rule can be putinto place that may prevent a clinician from remotely disabling an alarmif the clinician is, for example, more than some threshold distance awayfrom the patient.

The location information provided by the system illustrated in FIG. 20can also be used to provide alerts to clinicians when a patient 2010,2012 strays more than some threshold distance from the monitoring deviceassigned to the patient. While some examples of location-based ruleshave been discussed in the context of patient monitoring systems, theinformation provided by the system illustrated in FIG. 20 can be used toimplement a variety of location-based rules for many different kinds ofmedical devices. Such location-based rules can include, for example, anyrule for determining an action to be performed where the selected actionis dependent in whole, or in part, upon the estimated physical locationof a device, clinician, and/or patient.

In some embodiments, location-based rules can also be provided forconfiguring the medical devices 2002, 2004 (e.g., to configure patientmonitoring settings). For example, patient monitoring devices of thetype described herein are sometimes configured with differentphysiological parameter alarm limits depending upon the patient wardthat they are located in. For example, alarm limits for the pulse ratesof neonates should generally be set differently than for the pulse ratesof adults. Therefore, it may be desirable to provide a notification to aclinician if an attempt is made to monitor a patient located outside ofthe nursery using a monitoring device whose alarm limits have been setfor neonates. This can be done since the location of the medical devicecan be detected by the system illustrated in FIG. 20. Other monitoringdevice configuration settings can also be recommended to clinicians, orautomatically set, based upon the physical location of the monitoringdevice. In some embodiments, the configuration settings and techniquesdisclosed in US Patent Publication 2009/0275844, the entire contents ofwhich are hereby incorporated by reference herein, can be controlledusing the location-based rules described herein.

FIGS. 21-23 illustrate proximity displays 2100, 2200, 2300 that featurea multi-sided animation that appears to rotate from a first screen to apreferred screen in response to user proximity. This featureadvantageously provides feedback to the user that the monitor hasreceived an identification signal from the user, as described above, andhas recognized the user's presence. As examples, the multi-sidedpresentation may be any of a triangular-shaped, a cubic-shaped or aplanar solid having multiple facets and a different screen preference ontwo or more of the facets. One of ordinary skill will recognize thatmany other rotating geometric shapes can provide similar user feedback,including un-faceted shapes such as a sphere or cylinder. Thesemulti-sided presentations are described in further detail below.

FIGS. 21A-F illustrate a proximity display 2100 embodiment that utilizesa rotating triangular solid 2105 to depict transitions between multiplescreens that correspond to different display preferences of monitorusers that enter or exit proximity to the monitor. In particular, thetriangular solid 2105 has a first side 2101, a second side 2102 and athird side 2103 configured to display different user preferences ofpatient monitoring information in response to user proximity to thedisplay. Further, the triangular solid 2105 is shown to rotate during atransition between the sides 2101, 2102, 2103 so as to provide feedbackto a proximate user.

As shown in FIG. 21A, the first side 2101 relating to a first user isshown in the display 2110. As shown in FIG. 21B, when a second user isproximate the display, the monitor identifies the second user, asdescribed with respect to FIG. 7 below, and virtually rotates thetriangular solid 2105 from the first side 2101 to the second side 2102.As shown in FIG. 21C, the display 2110 then shows the second side 2102,corresponding to the second user's display preference. As shown in FIG.21D, when a third user enters proximity to the monitor, the monitoridentifies the third user and virtually rotates the triangular solid2105 from the second side 2102 to a third side 2103. As shown in FIG.21E, the display 2110 then shows the third side 2103, corresponding tothe third user's display preference. As shown in FIG. 21F, when thefirst user is again identified, the display 2110 virtually rotates thetriangular solid back to the first side 2101. In this manner, the sides2101, 2102, 2102 of the triangular solid 2105 are alternatively shown onthe display 2110 according to different user preferences and based uponuser proximity to the monitor. As described with respect to FIG. 13 ifseveral users are in proximity to the monitor at once, then priority oracknowledgement schemes are utilized to determine which screen todisplay.

FIGS. 22A-E illustrate a proximity display 2200 embodiment that utilizesa rotating cube 2205 to depict transitions between multiple screens thatcorrespond to different display preferences of monitor users that enteror exit proximity to the monitor. In particular, the cube 2205 has afirst side 2201, a second side 2202 and a third side 2203 configured todisplay different user preferences of patient monitoring information inresponse to user proximity to the display. Further, the cube 2205 isshown to rotate during a transition between the sides 2201, 2202, 2203so as to provide feedback to a proximate user, in a manner similar tothat described in detail with respect to FIGS. 21A-F, above.

FIGS. 23A-C illustrate a proximity display 2300 embodiment that utilizesa rotating planar solid 2305 to depict transitions between multiplescreens that correspond to different display preferences of monitorusers that enter or exit proximity to the monitor. In particular, theplanar solid 2305 has a first side 2301 and a second side 2302configured to display different user preferences of patient monitoringinformation in response to user proximity to the display. Further, theplanar solid 2305 is shown to rotate during a transition between thesides 2301, 2302 so as to provide feedback to a proximate user, in amanner similar to that described in detail with respect to FIGS. 21A-Fand FIGS. 22A-E, above.

Although some features are described herein with respect to a bedsidemonitor, a proximity display is applicable to any monitoring device,medical or non-medical and at any location, such as at bedside or atcentral monitoring, such as a nurse's station. Further, a proximitydisplay is applicable during physiological data collection or othermonitor uses, such as historical data review, setting and verificationof alarm limits and installation of software updates by medicalpersonnel or equipment maintenance staff, to name a few.

Translation of Medical Communication Protocols to FacilitateCommunication Between Devices and Systems

Healthcare costs have been increasing and the demand forreasonably-priced, high-quality patient care is also on the rise. Healthcare costs can be reduced by increasing the effectiveness of hospitalinformation systems. One factor which may affect the efficacy of ahealth institution is the extent to which the various clinical computersystems employed at the health institution can interact with one anotherto exchange information.

Hospitals, patient care facilities, and healthcare providerorganizations typically include a wide variety of different clinicalcomputer systems for the management of electronic healthcareinformation. Each of the clinical computer systems of the overall IT ormanagement infrastructure can help fulfill a particular category oraspect of the patient care process. For example, a hospital can includepatient monitoring systems, medical documentation and/or imagingsystems, patient administration systems, electronic medical recordsystems, electronic practice management systems, business and financialsystems (such as pharmacy and billing), and/or communications systems,etc.

The quality of care in a hospital or other patient care facility couldbe improved if each of the different clinical computer systems acrossthe IT infrastructure were able to effectively communicate with eachother. This could allow for the exchange of patient data that iscollected by one clinical computer system with another clinical computersystem that could benefit from such patient data. For example, this mayallow decisions relating to patient care to be made, and actions to betaken, based on a complete analysis of all the available information.

In current practice, individual clinical computer systems can be, andoften are, provided by different vendors. As a result, individualclinical computer systems may be implemented using a proprietary networkor communication infrastructure, proprietary communication protocols,etc.; the various clinical computer systems used in the hospital cannotalways effectively communicate with each other.

Medical device and medical system vendors sometimes develop proprietarysystems that cannot communicate effectively with medical devices andsystems of other vendors in order to increase their market share and toupsell additional products, systems, and/or upgrades to the healthcareprovider. Thus, healthcare providers are forced to make enterprise orsystem-wide purchase decisions, rather than selecting the besttechnology available for each type of individual clinical computersystem in use.

One example where this occurs is in the area of life-saving technologyavailable for patient monitoring. For example, many different bedsidedevices for monitoring various physiological parameters are availablefrom different vendors or providers. One such provider may offer abest-in-class device for monitoring a particular physiologicalparameter, while another such provider may offer the best-in-classdevice for another physiological parameter. Accordingly, it may bedesirable in some circumstances for a hospital to have the freedom touse monitoring devices from more than one manufacturer, but this may notbe possible if devices from different manufacturers are incapable ofinterfacing and exchanging patient information. Accordingly, the abilityto provide reasonably-priced, high-quality patient care can becompromised. In addition, since each hospital or patient care facilitymay also implement its own proprietary communication protocols for itsclinical computer network environment, the exchange of information canbe further hindered.

The Health Level Seven (“HL7”) protocol has been developed to provide amessaging framework for the communication of clinical messages betweenmedical computer systems and devices. The HL7 communication protocolspecifies a number of standards, guidelines, and methodologies whichvarious HL7-compliant clinical computer systems can use to communicatewith each other.

The HL7 communication protocol has been adopted by many medical devicemanufacturers. However, the HL7 standard is quite flexible, and merelyprovides a framework of guidelines (e.g., the high-level logicalstructure of the messages); consequently, each medical device or medicalsystem manufacturer or vendor may implement the HL7 protocol somewhatdifferently while still remaining HL7-compliant. For example, the formatof the HL7 messages can be different from implementation toimplementation, as described more fully herein. In some cases, the HL7messages of one implementation can also include information content thatis not included in messages according to another HL7 implementation.Accordingly, medical devices or clinical computer systems that are allHL7-compliant still may be unable to communicate with each other.

Consequently, what is needed is a module that can improve thecommunication of medical messages between medical devices or systemsthat use different allowed implementations of an establishedcommunication protocol (e.g., HL7), thereby increasing the quality ofpatient care through the integration of multiple clinical computersystems.

FIG. 24A illustrates a first medical device 2405 and a second medicaldevice 2410 that communicate with one another via a translation module2415. The first medical device 2405 is configured to transmit andreceive messages according to a first allowed format or implementationof an accepted electronic medical communication protocol, while thesecond medical device 2410 is configured to transmit and receivemessages according to a second allowed format or implementation of theelectronic medical communication protocol. In some embodiments, thefirst and second protocol formats are different implementations of theHL7 communication protocol. Other electronic medical communicationprotocols besides HL7 can also be used.

The translation module 2415 receives input messages having the firstprotocol format from the first medical device 2405 and generates outputmessages to the second medical device 2410 having the second protocolformat. The translation module 2415 also receives input messages havingthe second protocol format from the second medical device 2410 andgenerates output messages to the first medical device 2405 having thefirst protocol format. Thus, the translation module 2415 enables thefirst and second medical devices 2405, 2410 to effectively andseamlessly communicate with one another without necessarily requiringmodification to the communication equipment or protocol implemented byeach device.

In certain embodiments, the translation module 2415 determines theprotocol format expected by an intended recipient of the input messagebased on, for example, the information in the input message or byreferencing a database that stores the protocol format used by variousdevices, and then generates the output message based on the protocolformat used by the intended recipient device or system. The outputmessage can be generated based upon a comparison with, and applicationof, a set of translation rules 2420 that are accessible by thetranslation module 2415.

The translation rules 2420 can include rules that govern how to handlepossible variations between formatting implementations within a commonprotocol. Examples of variations in formatting implementation of anelectronic medical communication protocol include, for example, thedelimiter or separator characters that are used to separate data fields,whether a particular field is required or optional, the repeatability ofportions of the message (e.g., segments, fields, components,sub-components), the sequence of portions of the message (e.g., theorder of fields or components), whether a particular portion of amessage is included, the length of the message or portions of themessage, and the data type used for the various portions of the message.

In certain embodiments, the translation rules 2420 define additions,deletions, swappings, and/or modifications that should be performed inorder to “translate” an input message that adheres to a first HL7implementation into an output message that adheres to a second HL7implementation. The output message can have, for example, differentformatting than the input message, while maintaining all, or a portionof, the substance or content of the input message.

In addition to translating between different implementations of a commonelectronic medical communication protocol (e.g., different formatting ofHL7 messages), the translation module 2415 can also be configured totranslate between input and output messages adhering to differentcommunication protocols. In some embodiments, the translation module2415 is capable of responding to and translating messages from, forexample, one medical communication protocol to a separate medicalcommunication protocol. For example, the translation module 2415 canfacilitate communication between messages sent according to the HL7protocol, the ISO 11073 protocol, other open protocols, and/orproprietary protocols. Accordingly, an input message sent according tothe HL7 protocol can be translated to an output message according to adifferent protocol, or vice-versa.

The operation of the translation module 2415 and the translation rules2420 will be described in more detail below. Various embodiments ofsystem architectures including the translation module 2415 will now bedescribed.

In certain embodiments, the first medical device 2405, the secondmedical device 2410, and the translation module 2415 are communicativelycoupled via connection to a common communications network. In someembodiments, the translation module 2415 can be communicatively coupledbetween the first medical device 2405 and the second medical device 2410(with or without a communications network) such that all messagesbetween the first and second medical devices 2405, 2410 are routedthrough the translation module 2415. Other architectures are alsopossible.

The first and second medical devices 2405, 2410 and the translationmodule 2415 can be included in, for example, a portion of thephysiological monitoring system 200 of FIG. 2 or the clinical networkenvironment 600 of FIG. 6 described above. In certain embodiments, theportion of the physiological monitoring system 200 comprises a portionof a messaging sub-system of the physiological monitoring system 200 forsupporting the exchange of data between the various clinical computersystems used in the hospital.

In certain embodiments, the translation module 2415 can facilitatecommunication across multiple networks within a hospital environment. Inother embodiments, the translation module 2415 can facilitatecommunication of messages across one or more networks extending outsideof the hospital or clinical network environment. For example, thetranslation module 2415 can provide a communications interface withbanking institutions, insurance providers, government institutions,outside pharmacies, other hospitals, nursing homes, or patient carefacilities, doctors' offices, and the like.

In some embodiments, the translation module 2415 of FIG. 24 can be acomponent of, for example, the patient monitoring system 200 describedherein. For example, the translation module 2415 can be communicativelycoupled with the hospital network 220 illustrated in FIG. 2. In suchembodiments, the translation module 2415 can facilitate the exchange ofpatient monitoring information, including, for example, physiologicalparameter measurements, physiological parameter trend information, andphysiological parameter alarm conditions between bedside medical monitordevices, nurses' monitoring stations, a Hospital or Clinical InformationSystem (which may store Electronic Medical Records), and/or many othermedical devices and systems. The translation module 2415 can enableseamless communication between different medical devices and systems,each of which may use a different implementation of an electronicmedical communication protocol such as, for example, the HL7communication protocol, within a clinical or hospital networkenvironment.

In certain embodiments, the translation module 2415 can also facilitatecommunication between a first medical device that is part of the patientmonitoring sub-system and a second medical device that is not part of,or is external to, the patient monitoring system 200. As such, thetranslation module 2415 can be capable of responding toexternally-generated medical messages (such as patient informationupdate messages, status query messages, and the like from an HIS or CIS)and generating external reporting messages (such as event reportingmessages, alarm notification messages, and the like from patientmonitors or nurses' monitoring stations).

In another embodiment, first and second medical devices 2405, 2410communicate with each other over a communication bus 2421. Communicationbus 2421 can include any one or more of the communication networks,systems, and methods described above, including the Internet, a hospitalWLAN, a LAN, a personal area network, etc. For example, any of thenetworks describe above with respect to FIGS. 1, 2, 6, 7, 19, etc. canbe used to facilitate communication between a plurality of medicaldevices, including first and second medical devices 2405, 2410,discussed above. One such embodiment is illustrated in FIG. 24B.

In FIG. 24B, first medical device 2405 provides a message to thecommunication bus 2421. The message is intended for receipt by thesecond medical device 2410; however, because first and second medicaldevices 2405, 2410 communicate according to different communicationprotocol format, second medical device 2410 is unable to process themessage.

Translation module 2415 monitors the communication bus 2421 for suchmessages. Translation module receives the message and determines thatfirst medical device 2405 is attempting to communicate with secondmedical device 2410. Translation module 2415 determines that messagetranslation would facilitate communication between first and secondmedical devices 2405, 2410. Translation module 2415 therefore utilizesan appropriate translation rule stored in a translation module 2420.Translation module 2420 can include a memory, EPROM, RAM, ROM, etc.

The translation module 2415 translates the message from the firstmedical device 2405 according to any of the methods described herein.Once translated, the translation module 2415 delivers the translatedmessage to the communication bus 2421. The second medical device 2410receives the translated message and responds appropriately. For example,the second medical device may perform a function and/or attempt tocommunication with the first medical device 2405. The translation module2415 facilitates communication from the second medical device 2410 tothe first medical device 2405 in a similar manner.

The first medical device 2405 and the second medical device 2410 can be,for example, any of the medical devices or systems communicativelycoupled to the hospital network 222 illustrated in FIG. 2. These medicaldevices or systems can include, for example, point-of-care devices (suchas bedside patient monitors), data storage units or patient recorddatabases, hospital or clinical information systems, central monitoringstations (such as a nurses' monitoring station), and/or cliniciandevices (such as pagers, cell phones, smart phones, personal digitalassistants (PDAs), laptops, tablet PCs, personal computers, pods, andthe like).

In some embodiments, the first medical device 2405 is a patient monitorfor communicatively coupling to a patient for tracking a physiologicalparameter (e.g., oxygen saturation, pulse rate, blood pressure, etc.),and the second medical device 2410 is a hospital information system(“HIS”) or clinical information system (“CIS”). In some embodiments, thepatient monitor can communicate physiological parameter measurements,physiological parameter alarms, or other physiological parametermeasurement information generated during the monitoring of a patient tothe HIS or CIS for inclusion with the patient's electronic medicalrecords maintained by the HIS or CIS.

In some embodiments, the first medical device 2405 is an HIS or CIS andthe second medical device 2410 is a nurses' monitoring station, asdescribed herein. However, the translation module 2415 can facilitatecommunication between a wide variety of medical devices and systems thatare used in hospitals or other patient care facilities. For example, thetranslation module 2415 can facilitate communication between patientphysiological parameter monitoring devices, between a monitoring deviceand a nurses' monitoring station, etc.

Using the translation module 2415, a patient monitoring sub-system, suchas those described herein (e.g., physiological monitoring system 200),can push data to the HIS or pull data from the HIS even if the HIS usesa different implementation of the HL7 protocol, or some other electronicmedical communication protocol.

In certain embodiments, the patient monitoring sub-system can beconfigured to push/pull data at predetermined intervals. For example, apatient monitor or clinician monitoring station can download patientdata automatically from the HIS at periodic intervals so that thepatient data is already available when a patient is connected to apatient monitor. The patient data sent from the HIS can includeadmit/discharge/transfer (“ADT”) information received upon registrationof the patient. ADT messages can be initiated by a hospital informationsystem to inform ancillary systems that, for example, a patient has beenadmitted, discharged, transferred or registered, that patientinformation has been updated or merged, or that a transfer or dischargehas been canceled.

In other embodiments, the patient monitoring sub-system can beconfigured to push/pull data to/from the HIS only when the HIS issolicited by a query. For example, a clinician may make a request forinformation stored in a patient's electronic medical records on the HIS.

In still other embodiments, the patient monitoring sub-system can beconfigured to push/pull data to/from the HIS in response to anunsolicited event. For example, a physiological parameter of a patientbeing monitored can enter an alarm condition, which can automatically betransmitted to the HIS for storing in the patient's electronic medicalrecords. In yet other embodiments, any combination of the above methodsor alternative methods for determining when to communicate messages toand from the HIS can be employed.

Example system architectures and example triggers for the communicationof messages involving the translation module 2415 have been described.Turning now to the operation of the translation module, FIGS. 25A-25Dillustrate an example medical message at different phases or steps of atranslation process. The translation process will be described in moredetail below in connection with FIGS. 26, 27A and 27B.

FIG. 25A illustrates an example ADT input message 2505 received by thetranslation module 2415 from an HIS. The ADT input message 2505 isimplemented according to the HL7 communication protocol and containsinformation related to the admission of a patient to a hospital. The ADTmessage 2505 includes multiple segments, including a message headersegment 2506, an event segment, a patient identification segment, apatient visit segment, role segments, a diagnosis segment, and multiplecustom segments.

In some embodiments, the message header (“MSH”) segment 2506 defines howthe message is being sent, the field delimiters and encoding characters,the message type, the sender and receiver, etc. The first symbol orcharacter after the MSH string can define the field delimiter orseparator (in this message, a “caret” symbol). The next four symbols orcharacters can define the encoding characters. The first symbol definesthe component delimiter (“˜”), the second symbol defines the repeatabledelimiter (“I”), the third symbol defines the escape delimiter (“\”),and the fourth symbol defines the sub-component delimiter (“&”). All ofthese delimiters can vary between HL7 implementations.

In some embodiments, the example header segment 2506 further includesthe sending application (“VAFC PIMS”), the receiving application(“NPTF-508”), the date/time of the message (“20091120104609-0600”), themessage type (“ADT˜A01”), the message control ID (“58103”), theprocessing ID (“P”), and the country code (“USA”). As represented by theconsecutive caret symbols, the header segment also contains multipleempty fields.

FIG. 25B illustrates the message header segment 2506 after it has beenparsed into fields or elements based on an identified field delimiter(the caret symbol). In certain embodiments, the parsed input messagecomprises an XML message that is configured to be transformed accordingto extensible stylesheet language transformation (XSLT) rules.

In certain embodiment, the parsed input message can be encoded. FIG. 25Cillustrates the parsed message header segment of the input message afterbeing encoded (e.g., using a Unicode Transformation Format-8 (“UTF-8”)encoding scheme).

The encoded message header segment shows some of the various data typesthat can be used in the message. For example, the sending application(“VAFC PIMS”) of the third parsed field and the receiving application(“NPTF-508”) of the fifth parsed field are represented using ahierarchic designator (“HD”) name data type. The date/time field (theseventh parsed field) is represented using the time stamp (“TS”) datatype. The processing ID field (the eleventh parsed field) is representedusing the processing type (“PT”) data type. The fields that do notinclude a data type identifier are represented using the string (“ST”)data type. Other possible data types include, for example, codedelement, structured numeric, timing quantity, text data, date, entryidentifier, coded value, numeric, and sequence identification. The datatypes used for the various fields or attributes of the segments can varybetween formatting implementations.

FIG. 25D illustrates an example output message 2510 from the translationmodule 2415 based on the example input message 2505 of FIG. 25A. Theoutput message 2510 includes a message acknowledgement segment 2512.

Turning to the operation of the translation module, the translationmodule 2415 can, for example, create, generate, or produce an outputmessage that is reflective of the input message based on an applicationof the set of translation rules 2420. In some embodiments, thetranslation module 2415 can, for example, translate, transform, convert,reformat, configure, change, rearrange, modify, adapt, alter, or adjustthe input message based on a comparison with, and application of, theset of translation rules 2420 to form the output message. In someembodiments, the translation module 2415 can, for example, replace orsubstitute the input message with an output message that retains thecontent of the input message but has a new formatting implementationbased upon a comparison with, and application of, the set of translationrules 2420.

FIG. 26 illustrates a translation process 2600 for generating an outputmessage based on an input message and a comparison with the set oftranslation rules 2420 associated with the translation module 2415. Thetranslation process 2600 starts at block 2602 where the translationmodule 2415 receives an input message from a first medical device.

At block 2604, the translation module 2415 determines the formattingimplementation of the input message and the formatting implementation tobe used for the output message. In certain embodiments, the inputmessage can include one or more identifiers indicative of the formattingimplementation. In some embodiments, the determination of the formattingimplementation can be made, for example, by analyzing the message itselfby identifying the delimiter or encoding characters used, the fieldorder, the repeatability of segments, fields, or components, the datatype of the fields, or other implementation variations. In certainembodiments, the translation module 2415 can separate or parse out theformatting from the content of the message (as shown in FIG. 25B) to aidin the determination of the formatting implementation. In someembodiments, the translation module 2415 determines the formattingimplementation of the input message by referencing a database thatstores the implementation used by each device with which the translationmodule 2415 has been configured to interface.

In certain embodiments, the determination of the formattingimplementation required by the output message can also be determinedfrom the input message. For example, the input message can include afield that identifies the intended recipient application, facility,system, device, and/or destination. The input message can alternativelyinclude a field that identifies the type of message being sent (e.g.,ADT message) and the translation module 2415 can determine theappropriate recipient from the type of message being sent and/or thesending application, device, or system. The translation module 2415 canthen determine the formatting implementation required by the intendedrecipient of the input message.

At decision block 2605, the translation module 2415 determines whether arule set has been configured for the translation from the identifiedformatting implementation of the input message to the identifiedformatting implementation to be used for the output message. The ruleset may have been manually configured prior to installation of thetranslation module software or may have been automatically configuredprior to receipt of the input message. If a rule set has already beenconfigured, then the translation process 2600 continues to block 2606.If a rule set has not been configured, then a rule set is configured atblock 2607. The configuration of the rule set can be performed asdescribed below in connection with FIGS. 28 and 29A-29D. The translationprocess 2600 then continues to block 2608.

At block 2606, the translation module 2415 identifies the pre-configuredrules from the set of translation rules 2420 that govern translationbetween the determined formatting implementation of the input messageand the formatting implementation of the output message. In someembodiments, the identification of the pre-configured rules can be mademanually.

At block 2608, the translation module 2415 generates an output messagebased on the configured rule set(s) of the translation rules 2420. Incertain embodiments, the output message retains all, or at least aportion of, the content of the input message but has the format expectedand supported by the intended recipient of the input message.

The translation rules 2420 can include, for example, unidirectionalrules and/or bidirectional rules. A unidirectional rule is one, forexample, that may be applied in the case of a message from a firstmedical device (e.g., 2405) to a second medical device (e.g., 2410) butis not applied in the case of a message from the second medical deviceto the first medical device. For example, a unidirectional rule couldhandle a difference in the delimiters used between fields for twodifferent formatting implementations of, for example, the HL7communication protocol. The translation module 2415 can apply a fielddelimiter rule to determine if the field delimiter is supported by theintended recipient of the input message. If the field delimiter of theinput message is not supported by the intended recipient, the fielddelimiter rule can replace the field delimiter of the input message witha field delimiter supported by the intended recipient.

For example, an input message from an input medical device can include aformatting implementation that uses a “caret” symbol (“A”) as the fielddelimiter or separator. However, the formatting implementationrecognized by the intended recipient medical device may use a “pipe”symbol (“I”) as the field delimiter. The translation module 2415 canidentify the field delimiter symbol used in the formattingimplementation recognized by the intended recipient medical device fromthe set of translation rules 2420 and generate an output message basedon the input message that uses the pipe field delimiter symbol insteadof the caret field delimiter symbol used in the input message. The ruleto substitute a pipe symbol for a caret symbol would, in this case, onlyapply to messages that are sent to a recipient device that recognizesthe pipe symbol as a field delimiter. This rule could be accompanied bya complementary rule that indicates that a caret symbol should besubstituted for a pipe symbol in the case of a message that is intendedfor a recipient device that is known to recognize the caret symbol asthe field delimiter.

Another unidirectional rule can handle the presence or absence ofcertain fields between different formatting implementations. Forexample, an input message from an input medical device can includefields that would not be recognized by the intended recipient medicaldevice. The translation module 2415 can generate an output message thatdoes not include the unrecognized or unsupported fields. In situationswhere an input message does not include fields expected by the intendedrecipient medical device, the set of translation rules 2420 can includea rule to insert null entries or empty “ ” strings in the fieldsexpected by the intended recipient medical device and/or to alert therecipient device of the absence of the expected field. The sender devicemay also be notified by the translation module 2415 that the recipientdevice does not support certain portions of the message.

Other unidirectional rules can facilitate, for example, the conversionof one data type to another (for example, string (“ST”) to text data(“TX”) or structured numeric (“SN”) to numeric (“NM”)), and the increaseor decrease in the length of various portions of the message.Unidirectional rules can also be used to handle variations inrepeatability of portions of the message. For example, the translationmodule 2415 can apply a field repeatability rule to repeated instancesof a segment, field, component, or sub-component of the message todetermine how many such repeated instances are supported by therecipient device, if any, and deleting or adding any repeated instancesif necessary. For example, a phone number field of a patientidentification segment can be a repeatable field to allow for entry ofhome, work, and cell phone numbers.

Bidirectional rules can also be used. Such rules may apply equally tomessages between first and second medical devices (e.g., 2405, 2410)regardless of which device is the sender and which is the recipient. Abidirectional rule can be used to handle changes in sequence, forexample. In certain implementations, an input message from an inputmedical device can include a patient name field, or fields, in which afirst name component appears before a last name component. However, theintended recipient medical device may be expecting an implementationwhere the last name component appears before the first name component.Accordingly, the set of translation rules 2420 can include abidirectional rule to swap the order of the first and last namecomponents when communicating between the two medical devices, orbetween the two formatting implementations. In general, field orderrules can be applied to determine whether the fields, components, orsub-components are in the correct order for the intended recipient andrearranging them if necessary. Other bidirectional rules can be includedto handle, for example, other sequential variations between formattingimplementations or other types of variations.

The translation rules 2420 can also include compound rules. For example,a compound rule can include an if-then sequence of rules, wherein a rulecan depend on the outcome of another rule. Some translation rules 2420may employ computations and logic (e.g., Boolean logic or fuzzy logic),etc.

As discussed above, the messages communicated over the hospital-basedcommunication network can employ the HL7 protocol. FIGS. 27A and 27Billustrate translation processes 2700A, 2700B in which HL7 messages arecommunicated between a HIS and a medical device over a hospital-basedcommunications network or a clinical network. The translation processes2700A, 2700B will be described with the assumption that the rulesgoverning “translation” between the first and second HL7 formats havealready been configured.

FIG. 27A illustrates a translation process 2700A in which thetranslation module 2415 facilitates communication of an HL7 message,such as the ADT message of FIG. 25A, from an HIS having a first HL7format to an intended recipient medical device, such as a patientmonitor or a clinician monitoring station, having a second HL7 format.

The translation process 2700A starts at block 2701, where thetranslation module 2415 receives an input message having a first HL7format from the HIS. In certain embodiments, the input message includesinformation regarding, for example, the admission of a patient and/orpatient identification and patient medical history information from anelectronic medical records database.

At block 2703, the translation module 2415 determines the formattingimplementation of the input message and the formatting implementation tobe used for the output message. These determinations can be made in asimilar manner to the determinations discussed above in connection withblock 2604 of FIG. 26.

At block 2705, the translation module 2415 identifies the rules thatgovern translation between the determined HL7 format of the inputmessage and the HL7 format of the output message and generates an outputmessage having the second HL7 format based on the identified rules. Incertain embodiments, the output message retains the content of the inputmessage sent by the HIS but has the format expected and supported by theintended recipient of the input message.

At block 2707, the translation module 2415 can output the output messageto the intended recipient over the hospital-based communicationsnetwork. In certain embodiments, the intended recipient can transmit anacknowledgement message back to the hospital information systemacknowledging successful receipt or reporting that an error occurred.

FIG. 27B illustrates a translation process 2700B in which thetranslation module 2415 facilitates communication of an HL7 message froma medical device, such as a patient monitor, having a first HL7 formatto an HIS having a second HL7 format. For example, the patient monitorcan transmit reporting event data m such as patient alarm data, to theHIS to store in the patient's electronic medical records.

The translation process 2700B starts at block 2702, where thetranslation module 2415 receives an input message having a first HL7format from the medical device. In certain embodiments, the inputmessage includes patient monitoring data or alarm data regarding one ormore physiological parameters of the patient being monitored for storagein an electronic medical records database associated with the HIS.

At block 2704, the translation module 2415 determines the formattingimplementation of the input message and the formatting implementation tobe used for the output message. These determinations can be made in asimilar manner to the determinations discussed above in connection withblock 2604 of FIG. 26.

At block 2706, the translation module 2415 identifies the rules thatgovern translation between the determined HL7 format of the inputmessage and the HL7 format of the output message and generates an outputmessage having the second HL7 format based on the identified rules. Incertain embodiments, the output message retains the content of the inputmessage sent by the medical device but has the format expected andsupported by the HIS.

At block 2708, the translation module 2415 can output the output messageto the hospital information system over the hospital-basedcommunications network. In certain embodiments, the HIS can transmit anacknowledgement message back to the medical device acknowledgingsuccessful receipt or reporting that an error occurred.

FIGS. 26, 27A and 27B described the operation of the translator module2415. FIGS. 28 and 29A-29D will be used to illustrate the description ofthe configuration of the translation rules 2420.

The translation rules 2420 can be implemented as one or morestylesheets, hierarchical relationship data structures, tables, lists,other data structures, combinations of the same, and/or the like. Incertain embodiments, the translation rules 2420 can be stored in localmemory within the translation module 2415. In other embodiments, thetranslation rules 2420 can be stored in external memory or on a datastorage device communicatively coupled to the translation module 2415.

The translation module 2415 can include a single rule set or multiplerule sets. For example, the translation module 2415 can include aseparate rule set for each medical device/system and/or for eachpossible communication pair of medical devices/systems coupled to thenetwork or capable of being coupled to the network. In some embodiments,the translation module 2415 can include a separate rule set for eachpossible pair of formatting implementations that are allowed under amedical communication protocol such as, for example, the HL7 protocol.

In certain embodiments, the translation rules 2420 can be manuallyinputted using, for example, the messaging implementation software tool2800 illustrated in FIG. 28. For example, the software developer for aparticular hospital network can determine the protocol message formatsused by the devices and/or systems that are or can be coupled to thehospital network and then manually input rules to facilitate“translation” between the various protocol message formats supported orrecognized by the devices and/or systems.

FIG. 28 illustrates an example screenshot from a messagingimplementation software tool 2800 for manually configuring translationrules 2420 to be used by the translation module 2415. The screenshotfrom the messaging implementation software tool 2800 illustrates variousparameters that may differ between formatting implementations of anelectronic medical communication protocol, such as HL7. The screenshotalso includes areas where a user can input information that defines, oris used to define, translation rules for converting between differentHL7 implementations. In some embodiments, the messaging implementationsoftware tool 2800 stores a variety of pre-configured rule sets based,for example, on known communication protocol implementations of variousmedical devices. In such embodiments, a user may configure one or moretranslation rules 2420 to be used in communications involving suchdevices by entering identification information, such as the devicemanufacturer, model number, etc. Based on this identificationinformation, the messaging implementation tool 2800 can identify apre-configured set of translation rules for communication with thatdevice.

In other embodiments, the translation rules 2420 can be automaticallygenerated. For example, the automatic generation of a new set, ormultiple sets, of rules can be triggered by the detection of a newlyrecognized “communicating” medical device or system on a network. Incertain embodiments, the automatic generation of a new set or multiplesets of rules can occur at the time a first message is received from orsent to a new “communicating” medical device or system coupled to thenetwork. In still other embodiments, the automatic generation of rulesets includes updating or dynamically modifying a pre-existing set ofrules.

The automatic generation of translation rule sets can be carried out ina variety of ways. For example, in some embodiments, the translationmodule 2415 can automatically initiate usage of a pre-configured set oftranslation rules 2420 based upon, for example, the make and model of anew device that is recognized on the network. In certain embodiments,the translation module 2415 can request one or more messages from thenew device or system and then analyze the messages to determine the typeof formatting being implemented, as illustrated by the automatic ruleconfiguration process 2900A of FIG. 29A. The automatic ruleconfiguration process 2900A starts at block 2901, where the translationmodule 2415 receives one or more messages from a detected medical deviceor system on the network. The messages can be received upon transmissionto an intended recipient medical device or system or in response to aquery sent by the translation module 2415 or another medical device orsystem coupled to the network.

At block 2903, the translation module 2415 determines the protocol ofthe one or more received messages by, for example, analyzing the messageor by consulting a database that indicates what communicationprotocol/format is implemented by each medical device or system on thenetwork. In certain embodiments, the translation module 2415 isconfigured to handle medical messages implemented using a single commonprotocol, such as HL7. Accordingly, if a determination is made that thereceived messages are implemented using a non-supported ornon-recognized protocol, the translation module can ignore the messagesreceived from the detected medical device or system, output an alert orwarning, or allow the messages to be sent without being translated.

At block 2905, the translation module 2415 determines the formattingimplementation of the received message(s). In certain embodiments, thereceived messages can include one or more identifiers indicative of theformatting implementation. In other embodiments, the determination ofthe formatting implementation can be made, for example, by analyzing themessage itself by checking field order, the delimiter or encodingcharacters used, or other implementation variations. In certainembodiments, the translation module 2415 can separate or parse out theformatting from the content of the message to aid in the determinationof the formatting implementation.

At block 2907, the translation module 2415 configures one or more rulesor rule sets to handle messages received from and/or sent to thedetected medical device or system. In certain embodiments, theconfiguration of the rules involves the creation or generation of newrules. In other embodiments, the configuration of the rules involves thealteration or updating of existing rules. The configured rules or rulesets can be included with the translation rules 2420. If a set of rulesalready exists for the formatting implementation used by the new deviceor system, then the configuration of new translation rules may not berequired. Instead, existing translation rules can be associated with thenew device or system for use in communication involving that device orsystem. In other embodiments, the translation module 2415 can create anew set of rules geared specifically for the new device or system or canmodify an existing set of rules based on subtle formatting variationsidentified.

In other embodiments, the translation module 2415 can generate testmessage(s) that may be useful in identifying the communication protocoland implementation used by a device or system. For example, thetranslation module can generate test messages to cause the newlydetected device or system to take a particular action (e.g., storeinformation) and then query information regarding the action taken bythe newly detected device to determine whether or how the test messagewas understood. This is illustrated by the automatic rule configurationprocess 2900B of FIG. 29B.

The automatic rule configuration process 2900B starts at block 2902,where the translation module 2415 transmits one or more test, orinitialization, messages to a remote device or system detected on anetwork. The test messages can be configured, for example, to instructthe remote device or system to take a particular action (e.g., storepatient information). In certain embodiments, the test messages can beconfigured to generate a response indicative of the type of formattingrecognized or supported by the remote device or system. In otherembodiments, the test messages can be configured such that only devicesor systems supporting a particular formatting implementation willunderstand and properly act on the test messages.

At block 2904, the translation module 2415 queries the remote device orsystem to receive information regarding the action taken based on thetest message sent to the remote device or system to determine whetherthe test message was understood. For example, if the test messageinstructed the remote device or system to store patient information in aparticular location, the translation module 2415 can query theinformation from the location to determine whether the test message wasunderstood. If the test message was not understood, the translationmodule 2415 can, for example, continue sending test messages of knownformatting implementations until a determination is made that the testmessage has been understood.

At block 2906, the translation module 2415 determines the protocol andformatting implementation based on the information received. As anexample, in certain embodiments, the test message can include aninstruction to store patient name information. The test message caninclude a patient name field having a first name component followed by asurname component. The translation module 2415 can then query the remotedevice or system to return the patient surname. Depending on whether thepatient surname or the first name is returned, this query can be usefulin determining information about the order of fields in the formattingimplementation being used by the remote device or system. As anotherexample, the test messages can instruct the detected device or system tostore repeated instances of a component. The translation module 2415 canthen query the device or system to return the repeated instances to seewhich, if any, were stored. This repeatability information can also beuseful in determining whether certain fields are allowed to be repeatedin the formatting implementation being used by the remote device forsystem, and, if so, how many repeated instances are permitted.

At block 2908, the translation module 2415 configures one or more rulesto handle messages received from and/or sent to the detected medicaldevice or system. For example, the rules can convert messages from themessage format used by a first medical device to that used by a secondmedical device, as described herein. In certain embodiments, theconfiguration of the rules involves the creation or generation of newrules. In other embodiments, the configuration of the rules involves thealteration or updating of existing rules. If a set of rules alreadyexists for the formatting implementation used by the new device orsystem, then the configuration of new translation rules may not berequired. Instead, existing translation rules can be associated with thenew device or system for use in communication involving that device orsystem.

FIGS. 29C and 29D illustrate automatic rule configuration processesperformed by the translation module 2415 for messages utilizing the HL7protocol. The HL7 protocol can be used, for example, to communicateelectronic messages to support administrative, logistical, financial,and clinical processes. For example, HL7 messages can include patientadministration messages, such as ADT messages, used to exchange patientdemographic and visit information across various healthcare systems.

The automatic rule configuration process 2900C illustrated in FIG. 29Cis similar to the process 2900A illustrated in FIG. 29A. At block 2911,the translation module 2415 receives one or more messages from an HL7medical device. At block 2915, the translation module 2415 determinesthe formatting implementation of the HL7 medical device from the one ormore messages received. As discussed above, the determination of theformatting implementation can be made, for example, by checking fieldorder or sequence, field delimiter characters, repeatability,cardinality, and other HL7 implementation variations.

At block 2917, the translation module 2415 configures one or more rulesto handle messages received from and/or sent to the HL7 medical device.In certain embodiments, the configuration of the rules involves thecreation or generation of new rules for the detected formattingimplementation. In other embodiments, the configuration of the rulesinvolves the dynamic alteration or updating of existing rules. If a setof rules already exists for the formatting implementation used by thenew HL7 medical device, then the configuration of new translation rulesmay not be required. Instead, existing translation rules can beassociated with the new HL7 medical device for use in communicationinvolving that device.

The automatic rule configuration process 2900D illustrated in FIG. 29Dis similar to the process 2900B illustrated in FIG. 29B. At block 2912,the translation module 2415 transmits one or more test, dummy, orinitialization messages to an HL7 medical device. In other embodiments,the translation module 2415 can cause one or more test messages to betransmitted to the new HL7 medical device from another HL7 medicaldevice. As described above, the test messages can include messageshaving known HL7 formats configured to determine whether the HL7 deviceunderstands the test messages. The test messages can include test ADTmessages, for example.

At block 2914, the translation module 2415 queries the HL7 medicaldevice to receive information regarding an action taken or informationstored in response to the test message. At block 2916, the translationmodule 2415 determines the formatting implementation of the HL7 devicebased on the information received. In certain embodiments, thetranslation module 2415 can analyze the information received todetermine whether the test message or messages were properly understood.If none of the test messages were properly understood, the translationmodule 2415 can send additional test messages having other known HL7formats and repeat blocks 2914 and 2916.

At block 2918, the translation module 2415 configures one or moretranslation rules to handle messages received from and/or sent to thedetected HL7 medical device. In certain embodiments, the configurationof the translation rules involves the creation or generation of newtranslation rules. In other embodiments, the configuration of the rulesinvolves the alteration or updating of existing rules. If a set oftranslation rules already exists for the formatting implementation usedby the new HL7 medical device, then the configuration of new translationrules may not be required. Instead, existing translation rules can beassociated with the new HL7 medical device for use in communicationinvolving that HL7 medical device.

The automatic rule configuration processes described above can betriggered by the detection of a network device or system by thetranslation module 2415. The medical devices referred to in FIGS.29A-29D can include any of the devices or systems illustrated in FIG. 2and discussed above.

In some embodiments, the automatic generation of translation rules canadvantageously occur post-installation and post-compilation of themessaging sub-system software, which includes the translation module2415. In certain embodiments, the automatic generation or dynamicmodification of the translation rules 2420 can occur without having torecompile or rebuild the translation module software. This feature canbe advantageous in terms of efficiently complying with U.S. Food andDrug Administration (“FDA”) requirements regarding validation ofsoftware used in healthcare environments.

Take, for example, a situation where a medical device manufacturer plansto use the translation module 2415 to facilitate communication between aparticular medical device or system that is to be installed in ahospital (e.g., a patient monitoring system, as described herein), orother patient care facility, and other devices or systems that arealready installed at the hospital (e.g., the HIS or CIS). Any softwarerequired for the operation of the new medical device to be installed maybe at least partially validated for FDA compliance prior to installationat the hospital despite the fact that, for example, the HL7implementations of other existing devices or systems at the hospital maystill be unknown. For example, any aspects of the software for the newmedical device that are dependent upon receiving messages from otherhospital devices can be validated pre-installation as being capable offully and correctly operating when the expected message format isreceived. Then, once the medical device is installed at the hospital,the validation of the software can be completed by showing that thetranslation module 2415 is able to provide messages of the expectedformat to the newly installed device. In this way, FDA validation taskscan be apportioned to a greater extent to the pre-installation timeframewhere they can be more easily carried out in a controlled manner ratherthan in the field.

In addition, the translation module 2415 can further help streamline FDAvalidation, for example, when a medical device or system is expected tobe installed at different hospitals whose existing devices use, forexample, different implementations of the HL7 protocol. Normally, thistype of situation could impose the requirement that the entirefunctionality of the software for the new medical device be completelyvalidated at each hospital. However, if the translation module 2415 isused to interface between the new medical device and the hospital'sexisting devices, then much of the software functionality could possiblybe validated a single time prior to installation, as just described.Then, once installed at each hospital, the software validation for themedical device can be completed by validating that correct messageformats are received from the translation module (the translation rulesfor which are field-customizable). This may result in making on-sitevalidation procedures significantly more efficient, which willadvantageously enable more efficient FDA compliance in order to bringlife-saving medical technology to patients more quickly by the use offield-customizable translation rules.

Patient Monitoring Reports

Devices and methods for monitoring physiological parameters such asblood oxygen saturation, pulse rate, blood pressure, and many others,are described herein. Such medical monitoring devices are oftenprogrammed with alarm limits to automatically detect when aphysiological parameter has a value that is, for example, outside therange of values considered safe or healthy for that particularphysiological parameter. In some embodiments, when such an alarmcondition is detected, various actions can be taken. For example, thebedside medical monitor can emit an audible or visual alarm. Inaddition, in some cases, after the alarm condition has persisted forsome set amount of time (e.g., 5 sec.), the alarm condition can bedisplayed at, for example, a central patient monitoring station, asdescribed herein. Moreover, if the alarm condition continues to persistfor some set amount of time (e.g., 10 sec.), the clinician assigned tocare for the patient who is experiencing the alarm condition can benotified by, for example, a pager or other notification device.

The number of detected alarm conditions is, of course, dependent uponthe settings for the alarm criteria that indicate an alarm condition. Insome embodiments, such alarm criteria can include a threshold value,which may indicate the boundary between values for a physiologicalparameter that are considered safe or normal, and those that areconsidered to indicate a medical condition which may require attentionfrom a clinician. The nearer such an alarm threshold is set to valuesthat are common for that particular physiological parameter in healthyindividuals under normal circumstances, the larger the number of alarmevents that will be expected to be detected. Generally speaking, thecloser the alarm criteria come to being satisfied by the normal expectedrange of values for a given physiological parameter, then the greaterthe odds of detecting any deviation from the normal range of values thatmay indicate that the patient is in need of some type of medicalintervention (e.g., administration of drugs, CPR, ventilator, etc.).This can be desirable in the sense that it becomes less likely that apatient will experience medical duress without triggering an alarm,which can be referred to as a false negative.

Reduction of false negatives does not come without a cost, however.Namely, alarm criteria for physiological parameters that are successfulin reducing false negatives may also increase the rate of falsepositives, where alarm conditions are detected even though the patientmay not be experiencing any clinically significant medical duress. Iffalse positives become too frequent, they can become burdensome toclinicians, who are responsible for investigating alarm conditions,resetting the monitoring devices from the alarm state, etc. In addition,frequent false positives can even put patients at risk by reducing theimportance assigned to alarm events by clinicians, whether consciouslyor subconsciously. Thus, it is desirable to determine alarm criteria formedical monitoring applications that strike a satisfactory balance thatlimits false negatives to an acceptable rate without unduly increasingfalse positive alarm events. In some cases, false positives may bepreferred to false negatives, especially in circumstances where theconsequences of a false negative would be severe to the patient. Such apreference for maintaining the occurrence of false negatives at arelatively low rate can be reflected in the choice of alarm limitcriteria. It is not necessarily the case, however, that false positivesare always preferred to false negatives. Moreover, alarm criteria thatmay be satisfactory for one type of patient may be unsatisfactory forother types of patients. The appropriate balance between false positivesand false negatives may vary for different medical monitoringapplications.

For example, in the case of blood oxygen saturation monitoring, typicalSpO2 values of healthy individuals may fall in the range of 95-100%.Therefore, if a patient monitoring device were configured with an SpO2alarm threshold of 94%, the number of false positive alarm events may berelatively high. In contrast, if the SpO2 alarm threshold were set at92%, then the number of false positives would likely be reduced, but thenumber of false negatives may increase beyond a satisfactory level insome medical monitoring applications. Therefore, devices and methods forproviding data that would aid in the selection of an alarm thresholdthat would reduce false positives while still maintaining falsenegatives at or below a satisfactory level would be very useful. Suchdevices and methods could be used for establishing alarm criteria for awide variety of physiological parameters.

FIG. 30 is an example graph 3000 of the distribution of alarm events fora given physiological parameter as a function of alarm limit values. Thegraph 3000 plots the number of detected alarm conditions versus a rangeof alarm limit values. The graph 3000 reflects, for example, ahypothetical situation where physiological parameter alarm data iscollected from a statistically-significant number of patients of aparticular type (e.g., cardiac patients) over the course of astatistically-significant period of time using a range of differentalarm limit values. Of course, the distribution of alarm events as afunction of alarm limit values will generally vary for differentphysiological parameters.

The graph 3000 shows a set of linearly increasing alarm limit values onthe x-axis. The corresponding number of detected alarm conditions foreach alarm limit value is plotted on the y-axis. As illustrated, forthis particular physiological parameter, the number of detected alarmconditions generally decreases as the alarm limit value is increased.Each bar in the graph 3000 may be representative of, for example, acombination of false positive alarm events and correctly detected alarmevents (e.g., detection of an alarm event when the patient was actuallyin need of medical assistance).

The dashed vertical line 3002 represents one possible alarm limitthreshold value. When the physiological parameter value is above thethreshold indicated by the dashed vertical line 3002, for example, analarm condition is detected, whereas when the physiological parametervalue is below the threshold, no alarm condition is detected. The dashedvertical line 3004 represents another possible alarm limit value.

As shown on the graph 3000, the illustrated alarm limit values 3002,3004 are only separated by two values on the x-axis. However, the numberof alarms detected using each of the two illustrated alarm thresholds3002, 3004 is approximately halved in going from the first alarmthreshold 3002 to the second alarm threshold 3004. Thus, in this case,the number of alarm thresholds is non-linearly related to variation inthe alarm limit values. This is illustrative of the realization that, insome cases, a hospital or other patient care facility could makerelatively small changes to the alarm criteria used in monitoring aphysiological parameter while disparately impacting the number ofdetected alarms and false positives. In some cases, the number ofdetected alarms could be significantly reduced, for example, by reducingthe number of false positives without necessarily increasing the risk offalse negatives in a clinically-significant way. Even if, however, nodisproportionate change in the number of false positives can be achievedwith a relatively small adjustment to alarm criteria (e.g., an alarmthreshold value), the techniques described herein may still be useful insome circumstances for incrementally reducing the number of falsepositives in a safe manner. Of course, changes to the alarm criteriaused for monitoring patients are not to be taken lightly; generallyspeaking, hospital administrators or other responsible personnel shouldauthorize any changes to alarm criteria.

In some embodiments, a device and/or system is provided for collectingmedical monitoring information from patients in a patient care domain.For example, the medical monitoring information can be collected from aclinically-significant number of patients over a clinically-significantperiod of time. In some embodiments, the patient care domain is a groupof patients of a similar type, or a group of patients who exhibitsimilar medical characteristics, conditions, defects, etc., and, assuch, can also be expected to undergo monitoring alarm conditions forsimilar reasons. For example, the patient care domain could consist of agroup of cardiac patients on a hospital floor, etc.

In some embodiments, a number of bedside patient monitors are used tocollect physiological signals from the patients. The raw physiologicalsignals can be processed by the bedside patient monitors. For example,the bedside patient monitors may perform averaging of the raw signals,filtering, etc. The bedside patient monitors may also performcomputations to calculate the value of a physiological parameter. Thebedside patient monitors may then output an indication of aphysiological parameter value (e.g., SpO2, pulse rate, blood pressure,etc.) and its trending over time. Physiological information such as theraw physiological signals, processed physiological signals, and/orcalculated physiological parameter values, for example, for each of thepatients can then be transmitted to, and stored by, for example, acentral repository. In some embodiments, this information is stored by anetworked database such as, for example, the round-robin database 722described herein. In some embodiments, the central repository can storemedical monitoring information for the patients in a particular domain(e.g., a hospital ward) over a period of time such as a week, or amonth, for example.

At the initial time of monitoring, an algorithm, or algorithms, may beapplied to the raw physiological signals, processed physiologicalsignals, and/or computed physiological parameter values for detectingwhether a first set of alarm criteria are satisfied. This can be doneby, for example, each bedside patient monitor for each patient in thepatient care domain. The first set of alarm criteria are, for example,those criteria implemented in the patient monitoring devices thatperform real-time monitoring functions to detect alarm conditions. Ifthe alarm criteria are satisfied, then an alarm can be generated, asdescribed herein. The central repository can also be used to store theoccurrences of alarm conditions for each patient.

In some embodiments, once a statistically-significant amount of patientmonitoring data has been collected at the central repository, areporting module can access the central repository and use these data tosimulate the alarm events that would have been detected had the patientmonitoring devices in the patient care domain used a different set ofalarm criteria than those that were actually used at the time ofmonitoring.

In some embodiments, the reporting module is used in conjunction withthe patient monitoring systems described herein (e.g., those shown inFIGS. 1, 2, 6, 7, 19, and others). In some embodiments, the reportingmodule is a server or other computing device communicatively coupled toa network of bedside patient monitoring devices, a central monitoringstation, a database, and other devices that can form a patientmonitoring system. The reporting module can include a processor foranalyzing patient monitoring data. The reporting module can alsoinclude, for example, electronic memory for storing patient monitoringdata.

In some embodiments, if the central repository includes, for example,physiological parameter trend data for each of the patients, then thereporting module can access the trend data and can re-analyze it using,for example, the same algorithm, or algorithms, previously used by thebedside patient monitoring devices for detecting whether alarm criteriaare satisfied. However, in this case a second alarm criteria can be usedthat is different from the first alarm criteria that was used to detectalarm conditions, for example, in real time when the patient monitoringdata was actually collected. In some embodiments, the reporting modulere-analyzes the stored patient monitoring data using multiple differentnew alarm criteria. Thus, the reporting module can generate informationshowing how the number of alarms detected changes as a function ofchanging alarm criteria.

FIG. 31 is a flow chart that illustrates a method 3100 for determiningthe variation in identified alarm conditions resulting from varyingalarm criteria. The method 3100 begins at block 3102 where physiologicalparameter data is collected from a group of patients in a patient caredomain. For example, the physiological parameter data can be collectedby a number of different bedside patient monitoring devices distributedthroughout a patient care facility. The collected physiologicalparameter data can include, for example, any type of informationrelevant to the physiological parameter being monitored and the patientfrom whom the physiological parameter data is being collected. Again,some examples of physiological parameter data that can be collected areraw physiological signals, processed physiological signals, calculatedvalues of a physiological parameter, etc.

At block 3104, the physiological parameter data is analyzed to identifyalarm conditions based upon a first set of alarm criteria. The alarmcriteria can be configurable so as to modify the physiologicalconditions that will trigger an alarm. In some embodiments, the analysisof the physiological parameter data is performed in substantiallyreal-time by, for example, the bedside patient monitoring devices inorder to detect alarm conditions as they occur. The alarm criteria willgenerally depend upon the particular physiological parameter beingmonitored. In some embodiments, the alarm criteria is a single thresholdvalue. In some embodiments, the alarm criteria includes multiplethreshold values that define, for example, an enclosed range of safe ornormal values for the physiological parameter. Other types of alarmcriteria can also be used.

At block 3106, the physiological parameter data is stored at, forexample, a central repository (e.g., the round-robin database 722). Insome embodiments, the central repository stores all, or substantiallyall, of the physiological parameter data that was collected at block3102. For example, the central repository can store a physiologicalinformation such as the raw physiological signals from each patient, orphysiological signals that have already been processed or altered tosome extent by, for example, the bedside patient monitoring devices. Inaddition, the central repository can store information about any alarmconditions that were detected for each patient at block 3104. Forexample, the central repository can store the timing and type of eachalarm condition for each patient.

At block 3108, the physiological parameter data that was previouslystored can be analyzed to identify alarm conditions based on a secondalarm criteria that is different from the first criteria used at block3104. This analysis can be performed by, for example, the reportingmodule described herein. If, for example, in the case of blood oxygensaturation monitoring, detected pulse oximetry signals were analyzed atthe actual time of monitoring using an alarm threshold of 94% oxygensaturation, then later at block 3108, the pulse oximetry signals can bere-analyzed using an alarm threshold of 93% oxygen saturation, or 92%oxygen saturation, etc. This analysis of the previously-collectedphysiological parameter data can be used to simulate the effect of a newalarm threshold in a riskless manner, since patients can still bemonitored at, for example, blocks 3102, 3104 using alarm criteria thatare already accepted and validated. This ability to simulate the effectof changing alarm criteria on the alarm conditions that are identifiedfrom physiological data is advantageous to hospitals and other patientcare facilities as a means of adjusting alarm criteria to bespecifically adapted for that particular hospital or patient carefacility. Specially adapted alarm criteria are advantageous becausealarm criteria that work well at one hospital, or for one type ofpatient, are not necessarily guaranteed to work well at anotherhospital, or for another type of patient. This can be due to differencesin the type of monitoring equipment that is used, differences in patientpopulation, differences in the type of medical care offered, differencesin medical procedures implemented by clinicians, etc.

In some embodiments, the algorithm, or algorithms, that are applied bythe reporting module to the collected physiological parameter data atblock 3108 are the same as, or substantially similar to, those whichwere applied at the time of monitoring in order to detect real-timealarm conditions, though this may not be required in all embodiments. Inaddition, in some embodiments, the physiological parameter data storedat the central repository is the same as, or substantially similar to,the physiological parameter data to which alarm detection algorithmswere applied by, for example, bedside patient monitors at the time ofcollection of the data. In this way, different alarm criteria can besimulated as if they had actually been used at the time of collection ofthe physiological parameter data to detect real-time alarm conditions.

At block 3110, the reporting module can analyze the effect of thesimulated alarm criteria on alarm conditions that are detected. Forexample, the reporting module can analyze the change, if any, in thenumber of detected alarm conditions using the new simulated alarmcriteria. This information can be provided for each patient and/or forthe combined group of patients, for example. In addition, the reportingmodule can analyze differences in the timing at which alarm conditionswere detected. Generally speaking, the reporting module can analyze anychange in the number, type, timing, duration, etc. of alarm conditionsthat are detected when using the second alarm criteria as compared tothe alarm conditions detected using the first alarm criteria that wereapplied at the time of monitoring.

At block 3112, the reporting module can output a report that identifies,explains, summarizes, or otherwise bears upon the effect of thesimulated alarm criteria. This report can be beneficial to, for example,hospital administrators in determining whether any changes to the alarmcriteria used by, for example, the bedside patient monitors arewarranted. For example, as described herein, in some circumstances thealarm criteria could be changed so as to reduce the number of falsepositives that are detected. The reporting module enhances the abilityof hospital administrators to make such decisions because it can provideinformation about the effect that such changes would have had if theyhad been previously implemented. Generally speaking, hospitaladministrators will have the final responsibility for determiningwhether changes to the alarm criteria can be safely made in order to,for example, reduce false positives without unacceptably increasingfalse negatives.

FIG. 32 illustrates an example report with a table 3200 showing howsimulated alarm criteria affect alarm detection events. The table 3200includes row entries for five different simulated alarm criteria, thoughany number of new alarm criteria could be simulated. The table 3200includes column entries for the number of alarms detected using eachsimulated alarm criteria. The number of alarms could be broken down, forexample, according to patient, or listed as a total sum of alarmsdetected for all of the patients for whom physiological parameter datawas collected.

The table 3200 also includes column entries for the change in the numberof alarms that were detected using each of the simulated alarm criteriaas compared to the number of alarms that were detected using the actualalarm criteria applied at the time of collection of the physiologicalparameter data. This change could be indicated as the difference in thenumber of alarms, the percent difference, etc.

Many other types of information and information formats exist forreporting the effect of the simulated alarm criteria. FIG. 32illustrates only an example report that could be generated by thereporting module based upon the simulated alarm criteria. It should beunderstood that such reports could include a wide variety of informationrelating to the impact of the simulated alarm criteria to help hospitaladministrators make a decision as to whether changes to alarm criteriashould be made. In addition, such reports can be presented in a widevariety of formats, including tables, charts, graphs, lists,spreadsheets, etc.

FIG. 33 is a flow chart that illustrates another method 3300 fordetermining the variation in identified alarm conditions that occur as aresult of varying alarm criteria. The method 3300 is similar to themethod 3100 illustrated in FIG. 31, however, the method 3300additionally involves determinations of, for example, the expectedeffect of simulated alarm limits on false positive alarms and falsenegative alarms.

The method 3300 can proceed through blocks 3302 and 3304 as describedabove with respect to the method 3100 and blocks 3102, 3104 illustratedin FIG. 31. At block 3306, however, the method 3300 further includescollection of medical intervention data. The medical intervention datacan include, for example, records of whether a patient required sometype of medical intervention at any point in time while thephysiological parameter was being monitored. Such medical interventionscould include, for example, the administration of a drug, attention froma physician or nurse (e.g., non-routine attention), attention from arapid response team, administration of a treatment or procedure, etc.The medical intervention data can also include any pertinent informationabout the medical intervention such as, for example, the type, the time,and the duration of the medical intervention, the medical cause thatnecessitated the intervention, relationship to detect alarm events, etc.

In some embodiments, the medical intervention data that is collected atblock 3306 is used to determine which, if any, of the alarm conditionsdetected at block 3304 were false positive alarms and/or which werealarms that represented true indications of medical duress. Later, thisinformation can be used, for example, to determine whether varioussimulated alarm criteria would have eliminated any identified falsepositive alarms or whether the simulated alarm criteria would haveresulted in non-detection of any alarms that actually did indicate aneed for medical intervention (e.g., resulting in a false negative). Inaddition, the medical intervention data can be used to identify falsenegatives and to determine whether simulated alarm criteria would haveresulted in detection of such false negatives. This information can beanalyzed and presented in a report to further aid hospitaladministrators in making a determination of whether to change alarmcriteria used by patient monitoring devices based upon simulated alarmcriteria, as described herein.

The medical intervention data can be obtained in a variety of ways. Forexample, medical intervention data can be recorded by clinicians asmedical interventions become necessary. These records can then bemanually imported into the central repository that also stores thecollected physiological parameter data. Medical intervention data can beautomatically imported into the central repository from the patient'selectronic medical record stored in, for example, a Hospital InformationSystem or a Clinical Information System. In some embodiments, thebedside patient monitoring devices can be configured so as to promptclinicians to enter medical intervention data, for example, after analarm is disabled. Other techniques for obtaining records of medicalinterventions can also be used.

If a record of a medical intervention that has been performed on behalfof the patient is, for example, temporally associated with the timing ofa detected alarm condition (e.g., they are separated by some length oftime less than a pre-determined threshold), this can be taken as a signof an accurately detected alarm condition. For example, if a detectedalarm condition is followed by a medical intervention relatively shortlythereafter, then it can be presumed that the alarm condition requiredmedical attention. If, however, a record of a medical intervention thathas been performed is not temporally associated with the timing of anydetected alarm condition for that patient, then this can be anindication of a false negative since the medical condition thatnecessitated the intervention did not trigger an alarm. Later in themethod 3300, after various new alarm criteria have been simulated, itcan be determined whether such simulated criteria would have detectedthe false negative, or whether the new simulated criteria would havestill detected the alarm condition that was accurately detected by thealarm criteria in place at the time of monitoring.

In some embodiments, medical intervention data can include an automatedestimation of whether or not a medical intervention for a given patienthas taken place. An estimation of whether or not a medical interventionwas required after an alarm detection event can be automatically madebased upon, for example, the length of time that a clinician spent withthe patient after responding to an alarm event, or whether a physiciancame to check on the patient within some time limit of a detected alarmevent. This information can be collected using the clinician proximitydetection devices and systems described herein. For example, in someembodiments, a patient monitoring device can start a timer after analarm detection event has occurred. If the presence of a physician(e.g., as identified by a clinician token, as described herein) isdetected within some predetermined amount of time, then an estimationcan be made that the physician visit was in response to the alarm event.As such, the physician visit can be identified as a medicalintervention. Similarly, a patient monitoring device can track theamount of time that a clinician (e.g., a nurse) spends in proximity tothe patient after silencing an alarm. If the amount of time with thepatient exceeds a certain threshold, then it can be inferred that sometype of medical intervention was necessary in response to the alarmevent.

In addition, an estimate of whether or not medical intervention wasrequired, for example, after an alarm event can be determined byanalyzing the physiological parameter data collected for that patient.For example, the reporting module can analyze the trend values for thephysiological parameter and determine whether the physiologicalparameter continued to worsen after the alarm event was detected. Insome embodiments, the reporting module can analyze the trend data todetermine whether the patient's condition, as indicated by the trendvalues of the physiological parameter, was worse 1 min. after the alarmdetection event, whether it was worse 5 min. later, and/or whether itwas worse 10 min. later. Different time limits can of course also beused. If such an analysis indicates that the patient's conditiondeteriorated after the alarm event was detected, then this can be takenas an indication that the alarm did in fact indicate that the patientwas experiencing medical duress and that the alarm was not a falsepositive.

As just described, the medical intervention data used in the method 3300can come from actual records of medical interventions that occurred.Alternatively, or additionally, the medical intervention data used inthe method 3300 can be estimated based upon factors such as, forexample, the amount of time clinicians spent with the patient in thewake of a detected alarm event or the behavior of the physiologicalparameter within some relevant time after a detected alarm event. Otherfactors and methods for estimating the occurrence of a medicalintervention can also be used. While medical intervention data thatresults from actual clinician records may be more accurate and reliable,some such occurrences of medical interventions may go unreported.Estimated medical intervention data can be useful since the relianceupon clinicians to maintain accurate records is reduced, though theestimates may be somewhat less reliable than actual clinician records.

At block 3308, the collected physiological parameter data and themedical intervention data can be stored in, for example, the centralrepository (e.g., the round-robin database 722) for later analysis bythe reporting module. The reporting module can include logic used forcorrelating the collected medical intervention data with the detectedalarm events. For example, the logic can include rules or criteria fordetermining whether or not a given medical intervention for a patientwas related to an alarm condition experienced by that patient. Forexample, in the case of medical intervention data obtained from actualclinician records, a particular medical intervention for a patient canbe correlated with a detected alarm event for that patient if themedical intervention and the alarm event occurred within a certainamount of time of one another. Other methods are also possible formatching medical intervention data with corresponding detected alarmevents that were possibly related to the medical intervention. Forexample, such a correlation can be based upon the type of medicalintervention that was performed and the type of physiological parameterfor which monitoring data has been obtained. Some medical interventionsmay be viewed as being particularly likely to be related to a specificphysiological parameter. In such cases, the reporting module logic maybe configured to make it more likely that such a medical interventionwill be marked as being correlated with alarm events triggered by thatphysiological parameter.

At block 3310, the reporting module analyzes the physiological parameterdata using second alarm criteria, for example, as described with respectto FIG. 31 (e.g., block 3108). At block 3312, the reporting module cananalyze any differences between those alarm conditions identified usingthe first alarm criteria versus those alarm conditions identified usingsimulated second alarm criteria. For example, after determining thealarm conditions that would have been detected by the second alarmcriteria, the reporting module can determine how many of the true alarmconditions that were correctly identified at the actual time ofmonitoring using the first alarm criteria would have still been detectedif the simulated alarm criteria had instead been implemented. It isdesirable that such true alarm conditions still be detected so as toavoid increasing the number of false negatives. Accordingly, informationregarding the number of true alarm conditions that would go undetectedusing a given simulated alarm criteria can be provided to hospitaladministrators to aid in determining whether a proposed change to thealarm criteria should be adopted.

In addition, the reporting module can analyze the effect of thesimulated alarm criteria on any false negatives that were identifiedbased on medical intervention data. In some embodiments, the reportingmodule determines whether the simulated alarm criteria would havedetected any false negatives that were not identified by the first alarmcriteria actually used by the patient monitoring devices. This can bedone, for example, by executing logic designed to determine whether anyalarm conditions detected using the simulated alarm criteria aretemporally correlated with a previously-identified false negative event.If, for example, an alarm condition identified by the simulated alarmcriteria precedes the timing of the identified false negative by someperiod of time less than a given threshold, then this can be taken as anindication that the alarm condition would have been an indicator of thefalse negative. Other logical tests can also be applied to correlatealarm conditions detected using the simulated alarm criteria with falsenegatives that have been identified based on medical intervention data.

At block 3314, the reporting module outputs a report that identifies,explains, summarizes, or otherwise bears upon the effect of thesimulated alarm criteria. In some embodiments, the report can provide anindication of the effect that the simulated alarm criteria would beexpected to have on not only the number of detected alarm events butalso the number, percentage, proportion, etc. of, for example,previously undetected false negatives that may have been detected usingthe simulated alarm criteria. The report can also include an indicationof, for example, the number, percentage, proportion, etc. of actualalarm conditions that were correctly identified using the first alarmcriteria but may not have been identified using the second alarmcriteria. The report can also include other information as well.

FIG. 34 illustrates an example report with a table 3400 showing howsimulated alarm criteria affect the total number of alarm detectionevents as well as how the simulated alarm criteria affect, for example,false negatives and false positives. The table 3400 is similar to thetable 3200 illustrated in FIG. 32, and includes row entries for fivedifferent simulated alarm criteria. The table 3400 includes columnentries for the number of alarms detected using each simulated alarmcriteria. The table 3200 also includes column entries for the change inthe number of alarms that were detected using each of the simulatedalarm criteria as compared to the number of alarms that were detectedusing the actual alarm criteria applied at the time of collection of thephysiological parameter data.

In addition, the table 3400 includes column entries for the estimatednumber or percentage of false negatives that previously went undetectedbut would have been detected using a particular simulated alarmcriteria. The table 3400 also includes column entries for the estimatednumber or percentage of true alarm conditions that were correctlyidentified using the first alarm criteria but would not have beenidentified using a particular simulated alarm criteria (i.e., new falsenegatives resulting from the simulated alarm criteria). These values canbe determined or estimated by the reporting module, as described herein.The table 3400 could also include information regarding change in falsepositives, for example, the number of false positives that were detectedby the first alarm criteria that would not have been detected by thesimulated alarm criteria, or vice versa.

Again, FIG. 34 illustrates only an example report that could begenerated by the reporting module based upon the simulated alarmcriteria. It should be understood that such reports could include a widevariety of information to help hospital administrators make a decisionas to whether changes to alarm criteria should be made. In addition,such reports can be presented in a wide variety of formats, includingtables, charts, graphs, lists, spreadsheets, etc.

In addition to simulating alarm criteria, as described herein, thereporting module can also simulate the effect of other configurationchanges in the bedside patient monitoring devices and/or a centralpatient monitoring station. For example, the reporting module cansimulate the effect of different alarm notification delay times. Asdiscussed herein, in some embodiments, when an alarm condition isdetected, bedside patient monitors may be configured to wait until apredetermined alarm notification delay time has elapsed beforetransmitting notification of the alarm event to either a clinician or toa central monitoring station. In addition, the central monitoringstation can likewise be configured to wait until a predetermined alarmnotification delay time has elapsed before actually transmitting anotification of the detected alarm to a clinician by, for example, apage or other notification method.

These notification delay times can be useful in reducing the frequencyof false positive alarm notification events when alarm conditions onlytransiently persist. Such transient alarm conditions may be triggeredby, for example, sudden exertion or emotion. The reporting module can beuseful in simulating the effect of differing notification delay times onalarm notification events. This can be useful because, for example,relatively slight modifications to the notification delay times couldresult in an important reduction in the number of false positives towhich clinicians must respond.

FIG. 35 is a flow chart that illustrates a method 3500 for determiningthe variation in alarm notification events that occurs as a result ofvarying alarm notification delay times. The method 3500 begins at block3502 where patients are monitored for physiological parameter alarmevents, as described herein.

The method 3500 proceeds to block 3504 where alarm notification eventsare identified based upon a first alarm notification delay time. Forexample, an alarm notification event may be a notification by a bedsidepatient monitor to a central monitoring station of an alarm condition.In this case, the first alarm notification delay time could be measuredas the elapsed time between when an alarm condition was detected at thebedside monitor and when notification of the alarm was sent to thecentral monitoring station. In addition, an alarm notification event maybe a notification from a patient monitoring device to a clinician of analarm condition. In this case, the first alarm notification delay timecan be measured as the elapsed time between when an alarm condition wasdetected and when the clinician was notified.

At the initial time of monitoring, an algorithm, or algorithms, may beapplied to the raw physiological signals, processed physiologicalsignals, and/or computed physiological parameter values for detectingwhether an alarm condition has persisted for the duration of the firstalarm notification delay time. This can be done by, for example, eachbedside patient monitor for each patient in the patient care domain. Ifan alarm condition persists for the duration of the first alarmnotification delay time, then an alarm notification event can berecognized.

At block 3506, physiological parameter data is collected and stored at,for example, a central repository (e.g., the round-robin database 722),as described herein. At block 3508, the physiological parameter data isre-analyzed by, for example, the reporting module using a second alarmnotification delay time that is different from the first alarmnotification delay time. If, for example, the first alarm notificationdelay time used by the patient monitoring device at block 3504 were 5sec., the physiological parameter data could be re-analyzed using analarm notification delay time of, for example, 6 sec., or 7 sec., etc.Shorter delay times could also be simulated.

In some cases, if the alarm condition is only transient in nature, arelatively small lengthening of the alarm notification delay time couldresult in the alarm condition ceasing before an alarm notification eventis generated. In this way, adjustment of the alarm notification delaytime can potentially safely reduce the number of alarm notificationevents to which clinicians must respond. This can in turn increase theeffectiveness of patient care by allowing clinicians to focus their timeon attending to alarm events that are non-transient. Of course, anychange to alarm notification delay times should generally be approved byhospital administrators or other responsible personnel to ensure that,for example, increases in the alarm notification delay times do notunacceptably put patients at risk by increasing the amount of elapsedtime between a detected alarm and the arrival of a clinician.

The analysis of the previously-collected physiological parameter data bythe reporting module can be used to simulate the effect of a new alarmnotification delay time in a riskless manner since patients can still bemonitored at, for example, blocks 3502, 3504 using a delay time that hasalready been accepted and validated. This ability to simulate the effectthat new alarm notification delay times would have, without necessarilyactually implementing them, is advantageous to hospitals and otherpatient care facilities as a means of adjusting alarm notification delaytimes to be specifically adapted for that particular hospital or patientcare facility. As described herein with respect to alarm criteria, achange in the alarm notification delay times may result in significantlyfewer alarm notification events without necessarily increasing the riskto patients.

At block 3510, the reporting module can analyze differences betweenclinician notification events that are detected using the first alarmnotification delay time as compared to those that are detected using thesecond alarm notification delay time. For example, the reporting modulemay determine whether the total number of alarm notification eventsdecreases or increases, and by how much, in response to a change in thealarm notification delay time. This information can be presented tohospital administrators in the form of tables, charts, spreadsheets,etc. to assist them in determining whether a change in the alarmnotification delay times implemented by the patient monitoring deviceswould be advantageous.

Clinician response time data can also be collected and stored foranalysis by the reporting module. Clinician response time can bemeasured as, for example, the elapsed time between when a clinician isnotified of an alarm condition and when the clinician arrives at thepatient's room to shutoff the alarm and check the patient's status. Thiselapsed time can be measured by, for example, the bedside patientmonitoring devices and transmitted to the central repository of data.Clinician response times can be stored for each clinician and/or for agroup of clinicians as a whole. As a result, the reporting module canoutput information regarding, for example, the maximum, minimum, andaverage response times for each clinician, and/or for a group ofclinicians as a whole. This data may be useful to hospitaladministrators as an indicator of the performance of an individualclinician, or a group of clinicians, in responding to monitoring alarmsin a prompt manner.

Display Features

FIGS. 36A-B illustrate displays having layout zones including zones forparameters 3610, a plethysmograph 3620, a prompt window 3630, patientinformation 3640, monitor settings 3650, monitor status 3660, userprofiles 3670, a parameter well 3680, pulse-to-pulse signal quality bars3690 and soft key menus 3695. Advantageously, each zone dynamicallyscales information for readability of parameters most important to theproximate user. Also, the prompt window 3630 utilizes layered messagingthat temporarily overwrites a less critical portion of the display.Further, the parameter well 3680 contains parameters that the proximateuser has chosen to minimize until they alarm. These and other displayefficiency features are described below.

FIGS. 37A-F illustrate displays that vary layouts and font sizesaccording to the number of installed parameters. Horizontal and verticaldisplay formats are shown for displaying eight parameters (FIG. 37A);seven parameters (FIG. 37B); six parameters (FIG. 37C); five parameters(FIG. 37D); four parameters (FIG. 37E); and three parameters (FIG. 37F).Advantageously, font size increases with fewer installed parameters.Further, parameter layout varies according to the number of rows andspacing according to the number of installed parameters. Also, theplethysmograph display increases in size with few installed parameters.In addition, font size of text information scales according to theamount of information displayed, e.g. patient name is displayed in asmaller font when date and time information is added.

FIGS. 38A-B illustrate displays 3800 having parameter wells 3810. Inparticular, parameter values are displayed in either a main displayportion or in a parameter well. Through a menu selection or by userprofile activated by user proximity, a parameter is minimized to theparameter well. Advantageously, one or more parameters in the parameterwell are displayed in a relatively small font. However, when a minimizedparameter alarms, it is removed from the parameter well and return in arelatively larger font to the main display.

FIGS. 39A-B illustrate enlarged parameter displays 3900, 3901 thatincrease the font size of alarming parameters. In normal conditions, allparameters are display in a same sized font. When an alarm occurs, theviolating parameter's actual value and limit values are displayed in alarger font and also blink to draw attention to the violation. Inanother embodiment, where all parameters are displayed at or near themaximum-sized font, then the alarming parameter will increase onlyslightly in size while all other parameters are reduced in size. Thus,the effect is an appearance that the alarming parameter is enlarged. Inan embodiment, if either a single parameter alarms (FIG. 39A) or allparameters alarm (FIG. 39B), the background color also blinks at thesame frequency so as to contrast with the blinking font, such as betweena red background color and a soft red background color.

FIGS. 40-43 illustrate additional display embodiments having variousadvantageous features. FIGS. 40A-B illustrate trend displays 4000 havingcolored alarm zones 4010 so that a user can readily identify thehistorical severity of a patient condition that triggers an alarm. FIG.41 illustrate displays that invert arrow keys to match the cursor. FIGS.43A-B illustrate trend displays and corresponding set-up screens.

FIG. 42 illustrates a display having user-selectable jump-screens. Inparticular, through a menu option choice, a user can choose one ofmultiple jump screens, such as the seven choices shown, that they canaccess from the home page. In an embodiment, the default behavior forthe button is the Trend-Toggle button 4231. Other buttons are AlarmLimits 4232, Compressed Waveform View or PI & PVI trend overlay 4233,Mode Sensitivity 4234, Patient Assess 4235, Parameter Detail Toggle 4236and User Profile Login 4237.

Information and signals described herein can be represented using any ofa variety of different technologies and techniques. For example, data,instructions, commands, information, signals, bits, symbols, and chipsthat can be referenced throughout the above description can berepresented by voltages, currents, electromagnetic waves, magneticfields or particles, optical fields or particles, or any combinationthereof.

The various illustrative logical blocks, modules, circuits, andalgorithm steps described in connection with the embodiments disclosedherein may be implemented as electronic hardware, computer software, orcombinations of both. To clearly illustrate this interchangeability ofhardware and software, various illustrative components, blocks, modules,circuits, and steps have been described above generally in terms oftheir functionality. Whether such functionality is implemented ashardware or software depends upon the particular application and designconstraints imposed on the overall system. Skilled artisans canimplement the described functionality in varying ways for eachparticular application, but such implementation decisions should not beinterpreted as causing a departure from the scope of the presentinvention.

Depending on the embodiment, certain acts, events, or functions of anyof the methods described herein can be performed in a differentsequence, may be added, merged, or left out all together (e.g., not alldescribed acts or events are necessary for the practice of the method).Moreover, in certain embodiments, acts or events may be performedconcurrently, e.g., through multi-threaded processing, interruptprocessing, or multiple processors, rather than sequentially.

The various illustrative logical blocks, modules, and circuits describedin connection with the embodiments disclosed herein can be implementedor performed with a general purpose processor, a digital signalprocessor (DSP), an application specific integrated circuit (ASIC), afield programmable gate array (FPGA) or other programmable logic device,discrete gate or transistor logic, discrete hardware components, or anycombination thereof designed to perform the functions described herein.A general purpose processor can be a microprocessor, conventionalprocessor, controller, microcontroller, state machine, etc. A processorcan also be implemented as a combination of computing devices, e.g., acombination of a DSP and a microprocessor, a plurality ofmicroprocessors, one or more microprocessors in conjunction with a DSPcore, or any other such configuration. In addition, the term“processing” is a broad term meant to encompass several meaningsincluding, for example, implementing program code, executinginstructions, manipulating signals, filtering, performing arithmeticoperations, and the like.

The steps of a method or algorithm described in connection with theembodiments disclosed herein can be embodied directly in hardware, in asoftware module executed by a processor, or in a combination of the two.A software module can reside in RAM memory, flash memory, ROM memory,EPROM memory, EEPROM memory, registers, hard disk, a removable disk, aCD-ROM, a DVD, or any other form of storage medium known in the art. Astorage medium is coupled to the processor such that the processor canread information from, and write information to, the storage medium. Inthe alternative, the storage medium may be integral to the processor.The processor and the storage medium can reside in an ASIC. The ASIC canreside in a user terminal. In the alternative, the processor and thestorage medium can reside as discrete components in a user terminal.

The modules can include, but are not limited to, any of the following:software or hardware components such as software object-orientedsoftware components, class components and task components, processes,methods, functions, attributes, procedures, subroutines, segments ofprogram code, drivers, firmware, microcode, circuitry, data, databases,data structures, tables, arrays, or variables.

In addition, although this invention has been disclosed in the contextof certain preferred embodiments, it should be understood that certainadvantages, features and aspects of the systems, devices, and methodsmay be realized in a variety of other embodiments. Additionally, it iscontemplated that various aspects and features described herein can bepracticed separately, combined together, or substituted for one another,and that a variety of combination and subcombinations of the featuresand aspects can be made and still fall within the scope of theinvention. Furthermore, the systems and devices described above need notinclude all of the modules and functions described in the preferredembodiments.

1-14. (canceled)
 15. A medical patient monitoring device for monitoringphysiological information, the medical patient monitoring devicecomprising: a first interface configured to receive physiologicalinformation associated with at least one patient; a second interfaceconfigured to communicatively couple to an electronic medical record forthe patient; and a processor configured to determine signal quality formeasurements of the physiological information and to determine an amountof the measurements of the physiological information to transmit to theelectronic medical record based on the signal quality.
 16. The medicalpatient monitoring device of claim 15, wherein the processor isconfigured to decrease the amount of the measurements of thephysiological information transmitted to the electronic medical recordif the signal quality decreases.
 17. The medical patient monitoringdevice of claim 15, wherein the processor is configured to decrease thefrequency of the measurements of the physiological informationtransmitted to the electronic medical record if the signal qualitydecreases.
 18. The medical patient monitoring device of claim 15,wherein the processor is configured to increase the amount of themeasurements of the physiological information transmitted to theelectronic medical record if the signal quality increases.
 19. Themedical patient monitoring device of claim 15, wherein the processor isconfigured to increase the frequency of the measurements of thephysiological information transmitted to the electronic medical recordif the signal quality increases.
 20. The medical patient monitoringdevice of claim 15, wherein the signal quality comprises a degree ofconfidence metric for the measurements of the physiological information.21. The medical patient monitoring device of claim 15, furthercomprising: a detector for detecting the physical presence of aclinician token, the clinician token being indicative of the identity ofa clinician, wherein the processor is configured to transmit themeasurements of the physiological information in response to detectionof the clinician token in proximity to the medical patient monitoringdevice.